Python Symbolic Regression (PySR) [Physics Informed Machine Learning]

Python Symbolic Regression (PySR) [Physics Informed Machine Learning]

Neural Implicit Flow (NIF) [Physics Informed Machine Learning]

Neural Implicit Flow (NIF) [Physics Informed Machine Learning]

Fourier Neural Operator (FNO) [Physics Informed Machine Learning]

Fourier Neural Operator (FNO) [Physics Informed Machine Learning]

Deep Operator Networks (DeepONet) [Physics Informed Machine Learning]

Deep Operator Networks (DeepONet) [Physics Informed Machine Learning]

Hamiltonian Neural Networks (HNN) [Physics Informed Machine Learning]

Hamiltonian Neural Networks (HNN) [Physics Informed Machine Learning]

Lagrangian Neural Network (LNN) [Physics Informed Machine Learning]

Lagrangian Neural Network (LNN) [Physics Informed Machine Learning]

Neural Network Control in Collimator 2.0 & New Educational Videos!!!

Neural Network Control in Collimator 2.0 & New Educational Videos!!!

Residual Networks (ResNet) [Physics Informed Machine Learning]

Residual Networks (ResNet) [Physics Informed Machine Learning]

Neural ODEs (NODEs) [Physics Informed Machine Learning]

Neural ODEs (NODEs) [Physics Informed Machine Learning]

Physics Informed Neural Networks (PINNs) [Physics Informed Machine Learning]

Physics Informed Neural Networks (PINNs) [Physics Informed Machine Learning]

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

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

AI/ML+Physics: Preview of Upcoming Modules and Bootcamps [Physics Informed Machine Learning]

AI/ML+Physics: Preview of Upcoming Modules and Bootcamps [Physics Informed Machine Learning]

AI/ML+Physics: Recap and Summary [Physics Informed Machine Learning]

AI/ML+Physics: Recap and Summary [Physics Informed Machine Learning]

Using sparse trajectory data to find Lagrangian Coherent Structures (LCS) in fluid flows

Using sparse trajectory data to find Lagrangian Coherent Structures (LCS) in fluid flows

AI/ML+Physics Part 5: Employing an Optimization Algorithm [Physics Informed Machine Learning]

AI/ML+Physics Part 5: Employing an Optimization Algorithm [Physics Informed Machine Learning]

The Future of Model Based Engineering: Collimator 2.0

The Future of Model Based Engineering: Collimator 2.0

AI/ML+Physics Part 4: Crafting a Loss Function [Physics Informed Machine Learning]

AI/ML+Physics Part 4: Crafting a Loss Function [Physics Informed Machine Learning]

AI/ML+Physics Part 3: Designing an Architecture [Physics Informed Machine Learning]

AI/ML+Physics Part 3: Designing an Architecture [Physics Informed Machine Learning]

AI/ML+Physics Part 2: Curating Training Data [Physics Informed Machine Learning]

AI/ML+Physics Part 2: Curating Training Data [Physics Informed Machine Learning]

AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]

AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]

Physics Informed Machine Learning: High Level Overview of AI and ML in Science and Engineering

Physics Informed Machine Learning: High Level Overview of AI and ML in Science and Engineering

Can we make commercial aircraft faster? Mitigating transonic buffet with porous trailing edges

Can we make commercial aircraft faster? Mitigating transonic buffet with porous trailing edges

A Neural Network Primer

A Neural Network Primer

Supervised & Unsupervised Machine Learning

Supervised & Unsupervised Machine Learning

A Machine Learning Primer: How to Build an ML Model

A Machine Learning Primer: How to Build an ML Model

Arousal as a universal embedding for spatiotemporal brain dynamics

Arousal as a universal embedding for spatiotemporal brain dynamics

New Advances in Artificial Intelligence and Machine Learning

New Advances in Artificial Intelligence and Machine Learning

Nonlinear parametric models of viscoelastic fluid flows with SINDy

Nonlinear parametric models of viscoelastic fluid flows with SINDy

[5/8] Control for Societal-Scale Challenges: Road Map 2030 [Technology, Validation, and Transition]

[5/8] Control for Societal-Scale Challenges: Road Map 2030 [Technology, Validation, and Transition]

[8/8] Control for Societal-Scale Challenges: Road Map 2030 [Recommendations]

[8/8] Control for Societal-Scale Challenges: Road Map 2030 [Recommendations]