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#Uncertainty Quantification

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The National Centre for Research Methods

Agent Based Modeling

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Explore agent-based modeling for social research, covering model creation, analysis, and documentation, with insights on time dynamics and data quality assessment.
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10 Lesons
2 hours 30 minutes
On-Demand
Free-Video
Seds Online

The Carbonate Forum - The Importance of Quantification in Carbonate Sedimentology

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Explore quantitative approaches in carbonate sedimentology, discussing uncertainty, numerical models, and interdisciplinary collaboration for improved geological understanding and interpretation.
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21 Lesons
47 minutes
On-Demand
Free-Video
Fields Institute

Misspecification, and Uncertainty Quantification in Differential Privacy

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Explore differential privacy's theoretical guarantees, misspecification issues, and uncertainty quantification methods. Gain insights into designing mechanisms and addressing implementation challenges.
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19 Lesons
32 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Trying to Make Sense of Control from Pixels

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Explores challenges in merging machine learning with control systems, focusing on autonomous vehicles using vision. Discusses uncertainty quantification, robust controller design, and performance guarantees.
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1 Lesons
55 minutes
On-Demand
Free-Video
Society for Industrial and Applied Mathematics

Graph-Based Methods for Reduced-Order Reservoir Simulation

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Explore graph-based approaches for reduced-order reservoir simulation, comparing interwell methods like GPSNet with CGNet, which mimics 3D grid connections. Learn about their setup, training, and generalization capabilities.
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1 Lesons
59 minutes
On-Demand
Free-Video
Alan Turing Institute

The Role of Computational Social Science in Policymaking - Session 6

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Expert panel explores computational social science's role in policymaking, discussing micro data, agent-based models, empirical validation, and applications in fisheries, energy, and digital twins to enhance decision-making processes.
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12 Lesons
56 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

The Effectiveness of Nonconvex Tensor Completion - Fast Convergence and Uncertainty Quantification

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Explores nonconvex optimization for tensor completion, proposing a two-stage algorithm with guaranteed success, linear convergence, and statistical accuracy. Discusses distribution characterization and confidence interval construction.
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16 Lesons
33 minutes
On-Demand
Free-Video
Alan Turing Institute

Learning-Based Multiscale Modelling: Computing, Data Science, and Uncertainty Quantification

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Explore machine learning frameworks for multiscale modeling in materials science, including Fourier and recurrent neural operators, to accelerate computations and bridge scales across multiple physics levels.
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1 Lesons
1 hour 4 minutes
On-Demand
Free-Video
Simons Institute

Federated and Collaborative Learning - Session 1

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Explore cutting-edge topics in federated learning, including data valuation, privacy, uncertainty quantification, and scaling to foundation models, presented by leading experts in the field.
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1 Lesons
48 minutes
On-Demand
Free-Video
Paul G. Allen School

Distributionally Robust Hypothesis Tests - IFDS 2022

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Explore distributionally robust hypothesis tests with Yao Xie, delving into advanced statistical methods for robust decision-making under uncertainty.
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1 Lesons
41 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

Quantifying the Uncertainty in Model Predictions Using Conformal Prediction

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Learn techniques for quantifying uncertainty in neural network predictions, focusing on conformal prediction as a versatile, statistically rigorous method applicable to classification and regression tasks.
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1 Lesons
33 minutes
On-Demand
Free-Video
Alan Turing Institute

Sequential Design Based on Mutual Information for Computer Experiments - Joakim Beck, KAUST

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Explore uncertainty quantification using Gaussian Process emulators for complex systems. Learn about sequential design methods, mutual information criteria, and applications in climate, tsunami, and earthquake modeling.
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19 Lesons
20 minutes
On-Demand
Free-Video
Alan Turing Institute

Known Boundary Emulation of Complex Computer Models - Ian Vernon, Cambridge

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Explore efficient methods for emulating complex computer models using Known Boundary Emulation, focusing on uncertainty quantification and applications in climate, tsunami, and earthquake problems.
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12 Lesons
26 minutes
On-Demand
Free-Video
Alan Turing Institute

Deep Gaussian Processes for Bayesian Inversion - Matt Dunlop, Courant

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Explore deep Gaussian processes for Bayesian inversion, covering theoretical foundations, numerical methods, and applications in uncertainty quantification for complex physical systems.
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7 Lesons
26 minutes
On-Demand
Free-Video
Alan Turing Institute

Pragmatically Ambitious Multiscale Global Temperature Reconstruction - Finn Lindgren, Edinburgh

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Explore pragmatic approaches to global temperature reconstruction using multiscale models, data sources, and statistical techniques for uncertainty quantification and bias correction.
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21 Lesons
41 minutes
On-Demand
Free-Video
Alan Turing Institute

Workshop on Probabilistic Numerical Methods - Panel Discussion

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Panel discussion exploring probabilistic numerical methods, covering topics like reference priors, robust uncertainty quantification, and Bayesian inversion methods for improved statistical inference and error quantification.
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5 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Uncertainty Quantification of Quantum Chemical Methods - IPAM at UCLA

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Explore uncertainty quantification in quantum chemistry, covering error estimation, benchmarking, and machine learning approaches for improved accuracy in computational methods.
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38 Lesons
42 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Deep Learning and Computations of PDEs by Siddhartha Mishra

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Explore deep learning applications in PDEs, uncertainty quantification, and optimization. Learn about operator learning, DeepOnet decomposition, and high-dimensional PDEs in this advanced lecture.
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17 Lesons
50 minutes
On-Demand
Free-Video
Hausdorff Center for Mathematics

Uncertainty Quantification for Kinetic Equations I

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Overview of uncertainty quantification for kinetic equations, covering Monte Carlo methods, multi-fidelity techniques, and stochastic Galerkin particle methods. Explores computational challenges and recent advancements in the field.
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13 Lesons
1 hour 4 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Learning Uncertainty-Aware Models of Defect Kinetics at Scale - IPAM at UCLA

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Explore advanced techniques for modeling metal properties, including energy landscape exploration, coarse-graining with uncertainty quantification, and descriptor-based approaches for capturing diverse material characteristics.
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1 Lesons
53 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Adaptive Computing and Multi-Fidelity Learning - IPAM at UCLA

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Explore adaptive computing and multi-fidelity learning for efficient optimization and uncertainty quantification in complex scientific workflows, with applications and scaling challenges discussed.
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1 Lesons
49 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Gaussian Process Approximation & Uncertainty Quantification for Autonomous Experiment

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Explore advanced Gaussian process techniques for function approximation, uncertainty quantification, and autonomous experimentation, addressing challenges and improving performance in real-world applications.
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1 Lesons
52 minutes
On-Demand
Free-Video
Hausdorff Center for Mathematics

Uncertainty Quantification for Kinetic Equations II

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Explore uncertainty quantification for kinetic equations, focusing on Monte Carlo methods, multi-fidelity approaches, and stochastic Galerkin particle techniques to address high-dimensional challenges.
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1 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Alan Turing Institute

Efficient and Effective Calibration of Spatio-Temporal Models - Dan Williamson & James Salter, Exeter

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Explore efficient calibration techniques for spatio-temporal models, focusing on uncertainty quantification and Gaussian Process emulation in complex physical systems like climate and natural disasters.
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1 Lesons
24 minutes
On-Demand
Free-Video
Alan Turing Institute

Deep and Multi-Fidelity Learning with Gaussian Processes

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Explore uncertainty quantification using Gaussian Process emulators for complex systems, focusing on deep learning and multi-fidelity approaches in climate, tsunami, and earthquake modeling.
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1 Lesons
25 minutes
On-Demand
Free-Video
Alan Turing Institute

High-Dimensional Hierarchical Models for Large-Scale Geophysical Applications

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Explore high-dimensional hierarchical models for geophysical applications, focusing on uncertainty quantification and Gaussian Process emulation in complex physical systems.
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1 Lesons
24 minutes
On-Demand
Free-Video
Alan Turing Institute

Variational Bayesian Approximation of Inverse Problems Using Sparse Precision Matrices

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Explore Variational Bayes as an efficient alternative to MCMC for solving inverse problems in PDEs, using sparse precision matrices and stochastic optimization for improved computational tractability.
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1 Lesons
1 hour 4 minutes
On-Demand
Free-Video
Alan Turing Institute

Uncertainty Quantification with Physics-Informed Machine Learning

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Exploring uncertainty quantification in physics-informed machine learning, focusing on architecture and learning approaches for scientific applications and complex real-world phenomena.
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1 Lesons
1 hour 3 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Introduction to Probability and Bayesian Inference - Lecture 1

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Explore probability fundamentals and Bayesian inference principles in this comprehensive lecture, laying the groundwork for advanced data assimilation techniques in weather and climate modeling.
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1 Lesons
1 hour 32 minutes
On-Demand
Free-Video
APS Physics

Collaborating with Mathematicians on Major Societal Challenges - Session B02

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Explore interdisciplinary collaborations between mathematicians and physicists addressing societal challenges, from quantum computing to climate science, through talks by leading researchers.
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6 Lesons
3 hours 6 minutes
On-Demand
Free-Video
MICDE University of Michigan

UQ for ML and ML for UQ - Uncertainty Quantification and Machine Learning in Physics-Based Modeling

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Explore the interplay between Uncertainty Quantification and Machine Learning in physics-based modeling, examining their roles in solving complex computational challenges across various applications.
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1 Lesons
57 minutes
On-Demand
Free-Video
Inside Livermore Lab

Uncertainty Quantification, Software Ecosystems, and Infrastructure Resilience - Technical Talk

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Explore uncertainty quantification, exascale software ecosystems, and infrastructure resilience in this technical talk by Sarah Osborn at WiDS Livermore 2024.
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1 Lesons
15 minutes
On-Demand
Free-Video
Inside Livermore Lab

Uncertainty Quantification and Deep Learning for Water-Hazard Prediction

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Explore uncertainty quantification and deep learning techniques for predicting water hazards, focusing on storm surge impacts and urban infrastructure damage assessment.
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29 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Inside Livermore Lab

Parameter Subset Selection and Active Subspace Techniques for Engineering and Biological Models

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Explore parameter subset selection and active subspace techniques for engineering and biological models, focusing on influential parameter isolation and uncertainty quantification in complex systems.
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29 Lesons
1 hour 2 minutes
On-Demand
Free-Video
Isaac Newton Institute for Mathematical Sciences

From Quantum Entanglement to Future Data-Driven Engineering - Rothschild Lecture

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Explore high-dimensional Bayesian statistics in engineering, focusing on efficient data-physical model integration and uncertainty quantification. Learn about multilevel MCMC and measure-transport approaches.
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1 Lesons
1 hour 5 minutes
On-Demand
Free-Video
Isaac Newton Institute for Mathematical Sciences

Uncertainty Quantification for Bayesian Inverse Problems - Efficient Methods in the Small Noise Regime

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Explore efficient methods for uncertainty quantification in Bayesian inverse problems, focusing on small noise regimes and data-driven engineering applications.
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1 Lesons
57 minutes
On-Demand
Free-Video
Probabilistic AI School

Better Priors for Everyone - Keynote

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Explore advanced techniques for improving prior distributions in probabilistic models, enhancing Bayesian inference across various applications.
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1 Lesons
1 hour 1 minute
On-Demand
Free-Video
Prof. Ryan C. Cooper

ME3255 - Quantitative Descriptions on Monte Carlo Models

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Explore Monte Carlo models through quantitative descriptions, enhancing understanding of statistical simulation techniques and their applications in engineering and science.
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1 Lesons
25 minutes
On-Demand
Free-Video
Finnish Center for Artificial Intelligence FCAI

Bayesian Inference of Causal Graphs: Current Status and Future Directions

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Explore Bayesian inference for causal discovery, examining recent progress, challenges, and assumptions in modeling cause-effect relationships from observational data.
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1 Lesons
48 minutes
On-Demand
Free-Video
Uncertainty in Artificial Intelligence

Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning - Session 2

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Explore critical analysis of uncertainty quantification in machine learning, examining conditional entropy and mutual information as measures for aleatoric and epistemic uncertainty.
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1 Lesons
28 minutes
On-Demand
Free-Video
Uncertainty in Artificial Intelligence

Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty - UAI 2023 Oral Session 2

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Explore the effectiveness of credal set volume as a measure of epistemic uncertainty in binary and multi-class classification, highlighting implications for machine learning.
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1 Lesons
25 minutes
On-Demand
Free-Video
Bureau of Economic Geology

Geologic Interrogation of Photogrammetric Outcrop Reconstructions - Uncertainty and Mitigation

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Explore techniques for analyzing 3D outcrop reconstructions, focusing on visualization, data extraction, and interpretation strategies to enhance accuracy and reproducibility in geologic studies.
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1 Lesons
54 minutes
On-Demand
Free-Video
Alan Turing Institute

Beyond Tech - Machine Learning in Science & Policy - Professor David Dunson, Duke

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Exploring machine learning applications beyond tech, highlighting challenges in science and policy. Discusses fair algorithms, interpretable models, and the need for targeted methods in complex domains.
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10 Lesons
58 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Uncertainty-Aware Machine Learning Models of Many-Body Atomic Interactions

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Explore symmetry-aware machine learning models for atomic interactions, focusing on E(3)-equivariant neural potentials and Bayesian force fields for improved accuracy in materials modeling.
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23 Lesons
58 minutes
On-Demand
Free-Video
Simons Institute

Robust Equation Discovery and Sparse Sensing with Guarantees

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Explore statistical mechanics for robust sparse equation discovery and optimal sensor placement, with applications in nuclear digital twins and high-dimensional field reconstruction.
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1 Lesons
1 hour
On-Demand
Free-Video
International Centre for Theoretical Sciences

Data Assimilation and Dynamical Systems in Earth Sciences - Lecture 2

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Explore data assimilation in Earth sciences, focusing on dynamical systems and their applications in weather and climate modeling. Learn theoretical foundations and practical implementations.
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1 Lesons
1 hour 34 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Data Assimilation Experiments for Operational Weather Forecast in NARL

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Explore data assimilation techniques for operational weather forecasting, focusing on experiments conducted at NARL. Learn about integrating observations and short-range forecasts to improve atmospheric state estimation.
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1 Lesons
1 hour 8 minutes
On-Demand
Free-Video
Alan Turing Institute

Role of AI in Tackling Climate Change - How Uncertain is Future Sea Level Rise

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Explore AI's potential in addressing climate change, focusing on predicting sea level rise uncertainties, with insights from a leading expert in the field.
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1 Lesons
1 hour 1 minute
On-Demand
Free-Video
Society for Industrial and Applied Mathematics

Exploring Lagrangian Data Assimilation: Methods and Uncertainty - SIAM MPE Community Meeting

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Explore Lagrangian data assimilation methods and uncertainty in fluid dynamics. Learn about ensemble techniques, analytical solutions, and optimal tracer deployment for improved state estimation.
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3 Lesons
1 hour 4 minutes
On-Demand
Free-Video
Valence Labs

Training Neural Network Potentials: Bayesian and Simulation-based Approaches

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Explore advanced techniques for training neural network potentials in molecular dynamics simulations, including data-efficient methods, experimental data integration, and uncertainty quantification for reliable results.
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14 Lesons
1 hour 4 minutes
On-Demand
Free-Video
Interface Fluidics

New Microfluidic Methods for Advanced CCE

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Explore cutting-edge microfluidic techniques for PVT and CCE testing, extracting extensive data from minimal oil samples to enhance accuracy and efficiency in fluid analysis.
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1 Lesons
56 minutes
On-Demand
Free-Video
Valence Labs

Differentiable Simulations for Enhanced Sampling of Rare Events

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Explore deep learning applications in molecular simulations, including surrogate functions, sampling complex distributions, and time-propagation of differential equations. Learn about active learning, generative models, and reaction path finding.
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10 Lesons
1 hour 1 minute
On-Demand
Free-Video
UofU Data Science

Uncertainty, Prompting, and Chain-of-Thoughts in Large Language Models - Part 2

0 rewiews
Dive into advanced AI concepts including temperature scaling, Bayesian calibration, prompt-based finetuning, and chain-of-thought techniques for more reliable and explainable language models.
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11 Lesons
1 hour 21 minutes
On-Demand
Free-Video
ACM SIGPLAN

Bayesian Inference Using Probabilistic Programming

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Explore Bayesian inference techniques and probabilistic programming concepts with expert insights from Hong Ge at LAFI'24.
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1 Lesons
1 hour 2 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Machine Learning in Equation of State and Transport Modeling at Extreme Conditions

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Explore machine learning applications in equation of state and transport modeling for extreme conditions, enhancing accuracy and efficiency in material science and astrophysics research.
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20 Lesons
49 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

End-to-End Learning and Auto-Differentiation - Forces, Uncertainties, Etc.

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Explore deep learning and auto-differentiation in molecular simulations, covering surrogate functions, sampling distributions, and time-propagation of differential equations for scientific problem-solving.
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16 Lesons
56 minutes
On-Demand
Free-Video
Fields Institute

Machine Learning Approaches for Predicting Seismic, Acoustic and Atmospheric Data

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Explore machine learning techniques for predicting seismic, acoustic, and atmospheric data, focusing on KNN and neural networks with uncertainty quantification for improved accuracy.
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23 Lesons
41 minutes
On-Demand
Free-Video
Simons Institute

Generalization and Robustness in Offline Reinforcement Learning

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Explore offline reinforcement learning for safety-critical applications, covering generalization, robustness, and imitation learning in large-scale settings with rich function approximation.
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19 Lesons
54 minutes
On-Demand
Free-Video
Steve Brunton

SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning

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Explores SINDy-RL, a framework combining sparse identification of nonlinear dynamics with reinforcement learning for efficient, interpretable control policies in complex environments.
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9 Lesons
21 minutes
On-Demand
Free-Video
Alan Turing Institute

Some Thoughts on Gaussian Processes for Emulation of Deterministic Computer Models

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Explore Gaussian Process emulators for complex computer models in uncertainty quantification, focusing on theoretical aspects and applications to climate, tsunami, and earthquake problems.
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1 Lesons
54 minutes
On-Demand
Free-Video
Society for Industrial and Applied Mathematics

Numerical Simulation of Fractured Reservoirs

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Explore advanced techniques for simulating fractured reservoirs, including dual-porosity models, unstructured grids, and probabilistic approaches to enhance flow prediction and reservoir management.
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28 Lesons
48 minutes
On-Demand
Free-Video
Snorkel AI

Why Detecting Distributional Shift is So Hard and So Important

0 rewiews
Explore challenges and opportunities in detecting data distributional shift, a crucial aspect of AI robustness and reliability in real-world applications.
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1 Lesons
27 minutes
On-Demand
Free-Video
Neuro Symbolic

Uncertainty Quantification in Metacognition

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Explore uncertainty quantification in metacognition and its applications in AI research, focusing on DARPA-funded efforts and advancements in neuro-symbolic approaches.
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1 Lesons
28 minutes
On-Demand
Free-Video
Uncertainty in Artificial Intelligence

Human-in-the-Loop Mixup: Aligning Synthetic Data with Human Perception - Oral Session 2

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Explore human-aligned synthetic data in machine learning, focusing on mixup regularization. Discover how perceptual judgments and uncertainties can enhance model reliability and generalization.
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1 Lesons
26 minutes
On-Demand
Free-Video
Uncertainty in Artificial Intelligence

Probabilistic Circuits That Know What They Don't Know - UAI Oral Session 6

0 rewiews
Explore probabilistic circuits' robustness to out-of-distribution data and learn about tractable dropout inference for improved uncertainty quantification in a single forward pass.
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1 Lesons
27 minutes
On-Demand
Free-Video
Neuro Symbolic

Diversity Measures: Domain-Independent Proxies for Failure in Language Model Queries

0 rewiews
Explore domain-independent diversity measures to detect uncertainty in language model outputs, enhancing error detection and improving AI reliability.
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4 Lesons
12 minutes
On-Demand
Free-Video
Inside Livermore Lab

Leveraging Latent Representations for Predictive Physics-Based Modeling

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Explore advanced techniques for leveraging latent representations in predictive physics-based modeling, focusing on surrogate models, inverse problems, and transfer learning for complex PDEs.
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1 Lesons
56 minutes
On-Demand
Free-Video
Inside Livermore Lab

Derivative-Informed Neural Operators for Solving PDE-Governed Optimization Problems

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Explore novel machine learning for solving optimization problems with PDEs, featuring derivative-informed neural operators for efficient, scalable solutions in high-dimensional parameter spaces.
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1 Lesons
56 minutes
On-Demand
Free-Video
Inside Livermore Lab

How Could We Design Aligned and Provably Safe AI?

0 rewiews
Explore AI safety with Dr. Yoshua Bengio, focusing on run-time risk evaluation and Bayesian approaches to mitigate potential harm from advanced AI systems.
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1 Lesons
44 minutes
On-Demand
Free-Video
Georgia Tech Research

Inference and Uncertainty Quantification for Noisy Matrix Completion - Lecture 5

0 rewiews
Explore inference and uncertainty quantification for noisy matrix completion, focusing on de-biased estimators and their distributional characterizations for optimal confidence interval construction.
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1 Lesons
51 minutes
On-Demand
Free-Video
Finnish Center for Artificial Intelligence FCAI

Probabilistic Richardson Extrapolation

0 rewiews
Explore probabilistic Richardson extrapolation using Gaussian processes for accelerated convergence in numerical methods, with applications in cardiac modeling and statistical experimental design.
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1 Lesons
47 minutes
On-Demand
Free-Video
Institut des Hautes Etudes Scientifiques (IHES)

Uncertainty Quantification in Machine Learning: Federated Conformal Prediction

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Explore uncertainty quantification in machine learning through federated conformal prediction, enhancing model reliability and decision-making in distributed settings.
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1 Lesons
56 minutes
On-Demand
Free-Video
Google TechTalks

Robust Design Discovery and Exploration in Bayesian Optimization

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Explore data-driven methods for robust design discovery and optimization, focusing on Bayesian techniques that efficiently handle uncertainties and adversarial scenarios in various scientific domains.
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13 Lesons
53 minutes
On-Demand
Free-Video
Google TechTalks

High-Dimensional Prediction for Sequential Decision Making

0 rewiews
Explore efficient algorithms for online high-dimensional predictions, enabling no-regret guarantees, fairness, and uncertainty quantification in multiclass settings for improved decision-making.
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1 Lesons
49 minutes
On-Demand
Free-Video
nanohubtechtalks

The Materials Simulation Toolkit for Machine Learning (MAST-ML): Automating Development and Evaluation of Machine Learning Models for Materials Property Prediction

0 rewiews
Automate machine learning model development for materials property prediction using MAST-ML. Learn data import, feature engineering, model evaluation, and uncertainty quantification through hands-on activities.
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8 Lesons
51 minutes
On-Demand
Free-Video
Finnish Center for Artificial Intelligence FCAI

Explainable and Robust AI for VILMA Virtual Laboratory

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Explore explainable AI and uncertainty quantification in atmospheric research. Learn about SLISEMAP, a supervised manifold visualization method for local explanations and dimensionality reduction.
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18 Lesons
39 minutes
On-Demand
Free-Video
Neurosymbolic Programming for Science

Probabilistic Programming Tutorial - Part 2

0 rewiews
Explore advanced concepts in probabilistic programming, focusing on practical applications and techniques for scientific computing and data analysis.
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1 Lesons
1 hour 11 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

Uncertainty Quantification with Conformal Prediction - A Path to Reliable ML Models

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Dive into conformal prediction techniques for quantifying uncertainty in ML models, covering implementation across various domains and practical applications using Python and pre-trained neural networks.
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1 Lesons
1 hour 24 minutes
On-Demand
Free-Video
UofU Data Science

Probabilistic Machine Learning - Lecture 19

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Dive into advanced data science concepts through comprehensive lecture coverage of key theoretical and practical aspects in this graduate-level academic session.
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1 Lesons
1 hour 21 minutes
On-Demand
Free-Video
Inside Livermore Lab

Big Data Inverse Problems - Promoting Sparsity and Learning to Regularize

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Explore novel methods for solving big data inverse problems, focusing on sparse representation and L1 regularization. Learn about variable projection and deep neural networks for parameter optimization.
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1 Lesons
1 hour
On-Demand
Free-Video
Inside Livermore Lab

ML-driven Models for Material Microstructure and Mechanical Behavior - DDPS

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Explore ML-driven approaches for generating microstructures and accelerating material behavior analysis. Learn transfer learning techniques and rapid assessment methods for materials design optimization.
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1 Lesons
1 hour 8 minutes
On-Demand
Free-Video
Inside Livermore Lab

Data-Driven Modeling of Unknown Systems with Deep Neural Networks

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Explore data-driven modeling of unknown systems using deep neural networks. Learn to discover and approximate evolution operators for predictive analysis across various problem domains.
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1 Lesons
1 hour 15 minutes
On-Demand
Free-Video
Inside Livermore Lab

Physics-Enhanced Gaussian Processes for Learning of Electromechanical Systems

0 rewiews
Explore physics-enhanced Gaussian processes for modeling electromechanical systems. Learn about GP-PHS and physics-enhanced variational autoencoders to improve data efficiency and ensure physical correctness.
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1 Lesons
1 hour 15 minutes
On-Demand
Free-Video
Inside Livermore Lab

Challenges and Opportunities for Integrating Physics-Knowledge in Machine Learning Strategies

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Explore integrating physics knowledge into machine learning algorithms for improved generalization and physics-consistent predictions. Examine biases and strategies through a friction identification case study.
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1 Lesons
1 hour 10 minutes
On-Demand
Free-Video
Inside Livermore Lab

Probabilistic Methods for Data-Driven Reduced-Order Modeling

0 rewiews
Explore probabilistic methods for data-driven reduced-order modeling, including Gaussian process regression, deep kernel learning, and Bayesian reduced-order operator inference for efficient multi-query simulations and digital twinning.
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1 Lesons
1 hour 8 minutes
On-Demand
Free-Video
Inside Livermore Lab

AutoEncoders for Aerodynamic Predictions

0 rewiews
Explore autoencoders for aerodynamic predictions, focusing on flow past wing geometries. Learn about non-linear compression, latent representations, and uncertainty quantification in data-driven modeling.
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1 Lesons
1 hour 5 minutes
On-Demand
Free-Video
Inside Livermore Lab

Neural Differentiable Physics: Unifying Numerical PDEs and Deep Learning for Data-Augmented Computational Physics

0 rewiews
Explore Neural Differentiable Physics, unifying numerical PDEs and deep learning for enhanced computational modeling of complex physical systems. Learn innovative SciML approaches integrating physics principles with AI.
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1 Lesons
1 hour 28 minutes
On-Demand
Free-Video
Neurosymbolic Programming for Science

Probabilistic Programming Tutorial - Part 1

0 rewiews
Explore probabilistic programming fundamentals and applications with MIT expert Vikash Mansinghka in this comprehensive tutorial.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Simons Institute

Robust Optimization and Generalization

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Explore robust optimization's history and its modern machine learning applications, focusing on performance certification and practical challenges in ML systems.
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1 Lesons
1 hour 17 minutes
On-Demand
Free-Video
Isaac Newton Institute for Mathematical Sciences

Nematic Liquid Crystals: Where Mathematics Meets Physics and Applications

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Explore the fascinating intersection of mathematics, physics, and applications in nematic liquid crystals with Prof. Apala Majumdar's insightful lecture.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
VinAI

Generative Sequence Models for Sequential Decision Making

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Explore generative sequence models for decision-making under uncertainty. Learn how Transformer architecture and language modeling advances can enhance offline learning, online exploration, and multi-task generalization in AI.
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1 Lesons
1 hour 10 minutes
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Free-Video
Probabilistic AI School

Probabilistic Modeling and Programming Tutorial - Lecture 1

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Explore probabilistic modeling and programming techniques with expert guidance, enhancing your AI and machine learning skills through hands-on tutorials and practical examples.
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1 Lesons
1 hour 48 minutes
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Uncertainty in Artificial Intelligence

Geometric Probabilistic Models - Tutorial 4

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Explore geometric probabilistic models for data-efficient, uncertainty-aware decision-making in applications like drug design and robotics. Learn theory and implementation of Gaussian processes and related techniques.
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1 Lesons
2 hours 32 minutes
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Probabilistic AI School

Gaussian Processes

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Explore Gaussian Processes with Daniel Hernández-Lobato, covering key concepts, applications, and advanced techniques in probabilistic machine learning.
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1 Lesons
2 hours 22 minutes
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Free-Video