Sensitivity Analysis - Types of Sensitivity Analysis
Explore sensitivity analysis techniques, applications, and practical demonstrations to enhance data-driven decision-making and assess variable impacts on outcomes in various domains.
What's Next in Virus Detection and Vaccine Tech?
Explore cutting-edge virus detection methods, including wearable devices, and learn about vaccine technologies. Gain insights into the future of viral testing, telehealth, and precision health.
Thoughts on Rational Inference - Is Information Theoretic Inference Rational?
Exploring rational inference approaches for incomplete information in complex sciences. Discusses defining and implementing rational methods, handling misspecifications, and addressing model uncertainty and robustness.
The Laws of Sensitivity for Small Nonequilibrium Systems
Explore laws constraining sensitivity in small, nonequilibrium systems. Uncover mechanisms behind biochemical switches, sensors, and molecular discrimination, with implications for gene regulation models.
Introduction to Accounting and Finance for Civil Engineers
Learn essential accounting and finance principles for civil engineers, covering economic decision-making, risk analysis, bidding strategies, and financial management in construction projects.
Constrained and Unconstrained Optimization
Comprehensive exploration of optimization techniques, covering linear and nonlinear programming, integer programming, transportation problems, and multi-objective decision making.
Unmasking Clever Hans Predictors and Assessing Machine Learning - Spring 2021
Unmasking clever predictors: Explore Layer-wise Relevance Propagation and SPRAY techniques to assess machine learning models' decision-making processes and identify potential biases or faults.
Operations Research
Learn essential Operations Research techniques: linear programming, network analysis, integer programming, nonlinear optimization, game theory, Markov chains, and inventory management. Gain practical skills using AMPL software.
Sensitivity, Spatial Models, and Fokker-Planck Equations in Mathematical Oncology - Graduate Course
Dive into advanced mathematical concepts in oncology, exploring sensitivity analysis, spatial modeling, and Fokker-Planck equations with Dr. Thomas Hillen.
Linear Programming for Data Science - Data Science Tutorial
This video explains Linear Progression for Data Science with a variety of demonstrations & examples to help you learn this topic effectively and efficiently.
Excel - What If Analysis
Learn powerful Excel tools for data analysis, including sensitivity analysis, goal seek, scenario manager, and Solver add-in for optimizing complex problems.
Simulating Chemical Kinetics with ReactionMechanismSimulator.jl - JuliaCon 2021
Explore chemical kinetics simulation using ReactionMechanismSimulator.jl. Learn about mechanism analysis, symbolic reduction, and efficient steady-state solution identification in Julia.
Managing Uncertainty in Water Resource Modelling
Explore uncertainty analysis in water resource modeling, covering parameter selection, handling external uncertainties, model adaptation, and incorporating observations for improved predictions.
Epidemiology of COVID-19: Implications for Control
Explore COVID-19 epidemiology, data challenges, and control strategies with Harvard expert Marc Lipsitch. Gain insights on nowcasting, modeling, and key open questions in pandemic management.
Statistical Rethinking 2023 - Counts & Hidden Confounds
Explore hidden confounds in statistical analysis, sensitivity analysis, and poison counts. Learn about Simpson's paradox and its implications for data interpretation.
Statistical Rethinking 2022 - Counts & Confounds
Explore statistical rethinking with focus on counts and confounds. Learn about confounded admissions, sensitivity analysis, proxies, factors, and Poisson GLMs in this comprehensive lecture.
Shape Optimization Approach for Sharp-Interface Reconstructions in Inverse Problems
Shape optimization techniques for inverse problems: analyzing piecewise constant models, shape derivatives, and Lagrangian approaches. Applications in electrical impedance tomography and full waveform inversion.
Improving Insights by Utilizing Causal Inference Methods
Explore causal inference methods to de-bias data, approximate incremental improvements, and accelerate insights using propensity score matching and regression discontinuity.
Bayesian Workflow
Learn Bayesian workflow techniques for probabilistic modeling, including prior specification, model checking, and posterior predictive checks.
Partial Identification of Dose Responses with Hidden Confounders - UAI 2023 Oral Session 3
Explore novel methods for bounding continuous-valued treatment effects with hidden confounders in causal inference, enhancing decision-making in observational studies.
Masking Post-Quantum Cryptography - Part I
Explore cutting-edge post-quantum cryptography masking techniques, including zero tests, secure multiplication, and Kyber implementations, presented at CHES 2023.