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#Automatic Differentiation

Showing: 56 courses
The Julia Programming Language

Gradients for Everyone: A Quick Guide to Autodiff in Julia

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Explore automatic differentiation in Julia, comparing approaches with Python frameworks and learning to make code differentiable for various backends. Gain insights into forward and reverse modes, custom rules, and performance optimization.
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1 Lesons
30 minutes
On-Demand
Free-Video
The Julia Programming Language

The State of Julia in 2021 - JuliaCon Keynote

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Comprehensive overview of Julia's progress in 2021, covering threading, compiler improvements, linear algebra advancements, package updates, and future development plans.
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32 Lesons
43 minutes
On-Demand
Free-Video
The Julia Programming Language

Transformations and Automatic Differentiation in Computational Thinking - Lecture 3

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Explore transformations and automatic differentiation in Julia, covering linear and non-linear transformations, function types, and applications in machine learning, with practical examples and visualizations.
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20 Lesons
54 minutes
On-Demand
Free-Video
The Julia Programming Language

Loop Analysis and Vectorization in Julia - JuliaCon 2020

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Explore LoopVectorization.jl for efficient loop representation, cost modeling, and vectorization strategies in Julia, enhancing performance through intra-core parallelism and SIMD operations.
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15 Lesons
25 minutes
On-Demand
Free-Video
The Julia Programming Language

Flux - The Elegant Machine Learning Library for Julia

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Explore Flux, an intuitive machine learning library for Julia, featuring state-of-the-art performance, automatic differentiation, and innovative compiler technology for efficient and flexible ML development.
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30 Lesons
30 minutes
On-Demand
Free-Video
The Julia Programming Language

Tricks and Tips in Numerical Computing - Keynote

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Explore advanced numerical computing techniques, from complex differentiation to low-precision arithmetic, with insights on error analysis, matrix operations, and IEEE standards for improved computational accuracy and efficiency.
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40 Lesons
56 minutes
On-Demand
Free-Video
TensorFlow

Swift for TensorFlow - The Next-Generation Machine Learning Framework

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Explore language-integrated automatic differentiation and optimized tooling in Swift for TensorFlow, enhancing machine learning productivity and innovation.
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6 Lesons
31 minutes
On-Demand
Free-Video
The Julia Programming Language

Physics-Informed Automatic Differentiation in Scientific Simulations

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Explore how automatic differentiation intersects with physical symmetries and numerical analysis in scientific simulations, focusing on materials science applications in DFTK.jl.
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1 Lesons
10 minutes
On-Demand
Free-Video
The Julia Programming Language

Real-Time Airborne Magnetic Navigation with MagNav.jl

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Discover how MagNav.jl enables real-time magnetic navigation by compensating aircraft magnetic fields and implementing advanced navigation filters using Julia's powerful features.
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1 Lesons
27 minutes
On-Demand
Free-Video
MITCBMM

Computational Models of Cognition - Reverse-Engineering Common Sense in the Human Mind and Brain Pt 1

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Explore cognitive modeling to reverse-engineer human common sense, examining AI progress, scientific context, and probabilistic programming techniques for capturing learning and constructing models.
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15 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Alan Turing Institute

Physics-Constrained Reservoir-Computing for Turbulence and Chaotic Learning

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Explore physics-constrained reservoir-computing for turbulence and chaotic learning, combining physical principles with empirical modeling to predict and optimize complex fluid flows in aerospace propulsion and turbulence.
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1 Lesons
56 minutes
On-Demand
Free-Video
Society for Industrial and Applied Mathematics

Computational Optimal Transport - A Mini Tutorial

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Overview of novel approaches to compute optimal transport, blending recent techniques including convex optimization, automatic differentiation, and neural networks for large-scale approximations in high-dimensional regimes.
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1 Lesons
2 hours 12 minutes
On-Demand
Free-Video
IEEE

Programming Languages for High-Assurance Vehicles

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Explore secure programming for high-assurance vehicles using embedded domain-specific languages in Haskell, focusing on autopilot development, verification tools, and real-world applications.
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23 Lesons
30 minutes
On-Demand
Free-Video
Centre for Quantum Technologies

TensorCircuit - A Quantum Software Framework for the NISQ Era

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Explore TensorCircuit, an advanced quantum circuit simulator leveraging tensor networks and machine learning frameworks for enhanced quantum computing simulation and variational algorithms.
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1 Lesons
40 minutes
On-Demand
Free-Video
ACM SIGPLAN

Automatic Differentiation - Session Preview at POPL 2023

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Explore automatic differentiation techniques and their applications in programming languages, presented by expert Sasa Misailovic at POPL 2023.
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1 Lesons
10 minutes
On-Demand
Free-Video
ACM SIGPLAN

Synthesizing Precise Static Analyzers for Automatic Differentiation

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Explore Pasado, a technique for synthesizing precise static analyzers for Automatic Differentiation, improving precision in nonlinear operations and demonstrating applications in various domains.
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1 Lesons
17 minutes
On-Demand
Free-Video
ACM SIGPLAN

Probabilistic Programming with Programmable Variational Inference

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Explore a modular approach to variational inference in probabilistic programming, enhancing expressiveness and enabling user-defined objectives with systematic gradient estimation transformations.
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1 Lesons
21 minutes
On-Demand
Free-Video
Federated Learning One World Seminar

Federated Automatic Differentiation - Seminar 96

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Explore advanced concepts in federated automatic differentiation with Google researcher Zachary Charles, covering innovative approaches to distributed machine learning and privacy-preserving computation.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Yannic Kilcher

Efficient and Modular Implicit Differentiation - Machine Learning Research Paper Explained

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Explores a unified framework for implicit differentiation in machine learning, enabling automatic differentiation of optimization problems without manual derivations or loop unrolling, with applications in meta-learning and hyperparameter optimization.
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8 Lesons
33 minutes
On-Demand
Free-Video
AssemblyAI

JAX Crash Course - Accelerating Machine Learning Code

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Accelerate machine learning with JAX: Learn NumPy-like operations on CPU, GPU, and TPU, automatic differentiation, and high-performance techniques for ML research in this comprehensive introduction.
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11 Lesons
27 minutes
On-Demand
Free-Video
Association for Computing Machinery (ACM)

PyTorch - A Modern Library for Machine Learning with Adam Paszke

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Explore PyTorch's capabilities in machine learning, from research to production. Learn about its innovative solutions for efficient inference and its versatility across various ML scenarios.
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22 Lesons
1 hour 2 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Methods for Scalable Probabilistic Inference - IPAM at UCLA

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Explore scalable probabilistic inference methods for astrophysics, focusing on Gaussian Processes for time series analysis and open-source tools to accelerate Bayesian inference with large datasets.
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33 Lesons
46 minutes
On-Demand
Free-Video
Scala Days Conferences

GPU Accelerated Deep Learning for Scala 3 with Storch

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Discover Storch, a new PyTorch-based library for GPU-accelerated deep learning in Scala 3. Learn about tensor operations, automatic differentiation, and neural network APIs for building enterprise-grade machine learning applications.
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1 Lesons
43 minutes
On-Demand
Free-Video
PyCon US

The Fundamentals of Modern Deep Learning with PyTorch

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Learn PyTorch for deep learning: train neural networks for image and text classification, explore tensor operations, automatic differentiation, and modern libraries like PyTorch Lightning for efficient GPU training.
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1 Lesons
3 hours
On-Demand
Free-Video
Artem Kirsanov

The Most Important Algorithm in Machine Learning - Backpropagation Explained

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Explore backpropagation's fundamentals, from curve fitting to gradient descent, chain rule, and computational graphs. Gain insights into this crucial machine learning algorithm's principles and applications.
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12 Lesons
40 minutes
On-Demand
Free-Video
ACM SIGPLAN

Automatic Differentiation for Sparse Tensors

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Explore efficient automatic differentiation for sparse tensors, leveraging novel DSLs and optimizations to outperform existing frameworks in data-intensive applications.
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1 Lesons
15 minutes
On-Demand
Free-Video
ACM SIGPLAN

Abstract Interpretation for Automatic Differentiation

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Explore abstract interpretation for automatic differentiation, analyzing its application in machine learning, scientific computing, and graphics.
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1 Lesons
11 minutes
On-Demand
Free-Video
ACM SIGPLAN

Efficient CHAD - Optimizing Combinatory Homomorphic Automatic Differentiation

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Optimizar el algoritmo CHAD para diferenciación automática en modo reverso, logrando la complejidad computacional esperada mediante técnicas funcionales y paralelismo.
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1 Lesons
19 minutes
On-Demand
Free-Video
Strange Loop Conference

Symbolic Numeric Programming in Julia

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Explore Symbolics.jl for computer-algebra metaprogramming in Julia, enabling powerful code transforms, optimization, and automatic differentiation with symbolic techniques.
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1 Lesons
37 minutes
On-Demand
Free-Video
GOTO Conferences

Inside Every Calculus Is A Little Algebra Waiting To Get Out

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Explore algebraic approaches to automatic differentiation and integration in calculus, with Kotlin code examples. Learn how synthetic differential geometry simplifies complex mathematical concepts.
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1 Lesons
47 minutes
On-Demand
Free-Video
GOTO Conferences

Teaching New Tricks to Old Programs Part 2

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Explore advanced functional programming techniques for reinterpreting existing code, including hardware circuits, automatic differentiation, and interval analysis, using Haskell and GHC plugins.
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11 Lesons
31 minutes
On-Demand
Free-Video
GOTO Conferences

Teaching New Tricks to Old Programs Part 1

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Explore new interpretations for functional programs, including hardware circuits and automatic differentiation. Learn techniques for overloading lambda and organizing interpretations in Haskell.
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12 Lesons
30 minutes
On-Demand
Free-Video
PyCon US

Getting Started with Automatic Differentiation

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Explore automatic differentiation in Python, its applications in optimization and computational art, using libraries like JAX, TensorFlow, and PyTorch. Gain intuition for derivatives and gradients.
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8 Lesons
19 minutes
On-Demand
Free-Video
Scala Days Conferences

Differentiable Functional Programming

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Explore differentiable functional programming, covering supervised learning, gradient descent, and automatic differentiation techniques for efficient deep learning implementations in Scala.
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17 Lesons
34 minutes
On-Demand
Free-Video
The Julia Programming Language

BLASPhemy - Improving BLAS Handling in Enzyme.jl

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Optimizing BLAS and Lapack routines for Enzyme.jl, improving performance and reliability in numerical computations and machine learning applications within the Julia ecosystem.
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1 Lesons
24 minutes
On-Demand
Free-Video
Code Sync

Deep Dive in Nx Backends - Lecture 1

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Explore Nx Backends in Elixir, understanding their impact on performance and automatic differentiation. Learn about backend structure, runtime dispatching, and integration with Axon for deep learning.
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6 Lesons
23 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

Neural ODEs: Continuous-Time Models for Machine Learning - TMLS 2019

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Explore neural networks as implicit models and their applications in scientific computing with David Duvenaud at TMLS2019.
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1 Lesons
25 minutes
On-Demand
Free-Video
The Julia Programming Language

Strategies to Integrate Data and Biogeochemical Models

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Explore integrating data and biogeochemical models using Sindbad.jl framework. Learn hybrid approaches combining physics-based models with neural networks for ecosystem dynamics simulation.
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1 Lesons
11 minutes
On-Demand
Free-Video
The Julia Programming Language

ProcessSimulator.jl - A Differentiable Chemical Process Simulator

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Differentiable chemical process simulator leveraging symbolic transformations and automatic differentiation for robust flowsheeting, thermodynamic property calculations, and system-level optimization in Julia.
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1 Lesons
11 minutes
On-Demand
Free-Video
The Julia Programming Language

JSOSuite.jl - One-Stop Solution for Optimization

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Explore JSOSuite.jl, a comprehensive optimization package offering automatic solver selection, research-level algorithms, and flexible modeling interfaces for various problem types in Julia.
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1 Lesons
24 minutes
On-Demand
Free-Video
The Julia Programming Language

Recent Advances in EAGO.jl and its Use With JuMP.jl

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Explore EAGO.jl, an open-source global optimizer for MINLPs in Julia, and its integration with JuMP for enhanced accessibility and capabilities in solving complex optimization problems.
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1 Lesons
11 minutes
On-Demand
Free-Video
The Julia Programming Language

Recent Advances in Optimization Solvers within JuliaSmoothOptimizers

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Explore cutting-edge nonlinear optimization solvers in JuliaSmoothOptimizers. Learn about new packages, performance enhancements, and flexible implementations for large-scale problems using high-level linear algebra and automatic differentiation.
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1 Lesons
17 minutes
On-Demand
Free-Video
DataLearning@ICL

WarpPINN: Cine-MR Image Registration with Physics-Informed Neural Networks

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Explore WarpPINN, a physics-informed neural network for cardiac image registration. Learn how it quantifies local heart deformations, improving heart failure diagnosis through advanced strain estimation techniques.
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1 Lesons
58 minutes
On-Demand
Free-Video
Unify

Deep Dive: Gradients in Ivy - Tutorial 20

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Explore gradients in Ivy, mastering advanced techniques for deep learning and neural network optimization.
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1 Lesons
31 minutes
On-Demand
Free-Video
TensorFlow

Swift for TensorFlow - TF World '19

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Explore Swift for TensorFlow, a cutting-edge ML platform integrating deep neural networks with AI algorithms and software development, enhancing research efficiency and speed.
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7 Lesons
39 minutes
On-Demand
Free-Video
ACM SIGPLAN

Fast Deep Learning with Categories

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Explore GPU-accelerated deep learning using Haskell, ConCat, and Accelerate for high-performance industrial applications.
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1 Lesons
42 minutes
On-Demand
Free-Video
GERAD Research Center

Decision Awareness in Reinforcement Learning - End-to-End Optimization Approaches

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Explore decision awareness in reinforcement learning, covering control-oriented models, neural ODEs, and computational challenges. Gain insights into advanced techniques for optimal decision-making.
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25 Lesons
54 minutes
On-Demand
Free-Video
The Julia Programming Language

Molly.jl - Molecular Dynamics in Julia

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Explore Molly.jl for molecular dynamics simulations in Julia. Learn about its features, advantages, and applications in research, including differentiable molecular simulation and force field improvement.
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1 Lesons
30 minutes
On-Demand
Free-Video
The Julia Programming Language

AI Hardware and Real-world AI - JuliaCon 2024

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Explore AI's computational impact, from theoretical understanding to efficient hardware design. Gain insights on optimizing AI models for real-world applications across various computational scales.
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1 Lesons
52 minutes
On-Demand
Free-Video
NHR@FAU

LLVM in HPC: Enabling Performance Portability, Interoperability, and Novel Features - Part 2

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Explore recent LLVM efforts for HPC: portable CUDA, debugging at scale, GPU execution of legacy codes, automatic differentiation, ML in compilers, and static information impact.
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1 Lesons
55 minutes
On-Demand
Free-Video
The Julia Programming Language

FastIce.jl: A Massively Parallel Ice Flow Model Running on GPUs

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Explore FastIce.jl, a Julia-based ice flow model for GPUs. Learn about its modular architecture, performance on supercomputers, and applications in efficient large-scale ice sheet modeling.
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1 Lesons
33 minutes
On-Demand
Free-Video
Inside Livermore Lab

Scientific Uses of Automatic Differentiation - DDPS

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Explore automatic differentiation's scientific applications beyond machine learning. Discover innovative approaches in PDEs, self-assembly, fluid dynamics, and protein modeling using large-scale optimization.
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1 Lesons
1 hour 8 minutes
On-Demand
Free-Video
Inside Livermore Lab

Physics Informed Machine Learning through Symbolic Regression

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Explore symbolic regression for identifying PDE models from scarce, noisy data. Compare with Physics-Informed Neural Networks and discuss applications in fault detection and system health prognostics.
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1 Lesons
1 hour 9 minutes
On-Demand
Free-Video
GERAD Research Center

Decision Awareness in Reinforcement Learning

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Explore decision awareness in reinforcement learning, focusing on control-oriented transition models and neural ODEs for nonlinear trajectory optimization. Discuss computational challenges and scaling solutions.
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1 Lesons
1 hour 2 minutes
On-Demand
Free-Video
NHR@FAU

LLVM in HPC - Enabling Performance Portability, Interoperability, and Novel Features - Part 1

0 rewiews
Explore LLVM's impact on HPC, covering portable CUDA, debugging at scale, GPU execution of legacy code, and ML in compilers. Learn about efforts to enhance performance, tooling, and development in HPC.
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1 Lesons
1 hour 13 minutes
On-Demand
Free-Video
GERAD Research Center

PyTorch Tutorial for Deep Learning

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Explore PyTorch for deep learning: implement neural networks, leverage GPU acceleration, and train convolutional models for digit recognition using efficient coding practices.
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1 Lesons
2 hours
On-Demand
Free-Video