Learning Physics-guided Neural Networks with Competing Physics Loss: Solving Eigenvalue Problems Published 2021-04-12 Download video MP4 360p Recommendations 51:22 Rethinking Physics Informed Neural Networks [NeurIPS'21] 50:26 Tom Goldstein: "What do neural loss surfaces look like?" 1:01:11 Neural operator: A new paradigm for learning PDEs by Animashree Anandkumar 09:29 How Super Resolution Works 13:52 The Neural Network, A Visual Introduction | Visualizing Deep Learning, Chapter 1 31:33 The Oldest Unsolved Problem in Math 11:43 Scientific Machine Learning: Physics-Informed Neural Networks with Craig Gin 21:04 How Can Physics Inform Deep Learning Methods - Anuj Karpatne 03:06 Gradient Descent in 3 minutes 28:48 Matthieu Barreau - Physics-Informed Learning: Using Neural Networks to Solve Differential Equations 17:51 Eigenvalues and eigenstates in quantum mechanics 20:10 Physics Informed Neural Networks 50:13 Physics Guided Machine Learning: A New Framework for Accelerating Scientific Discovery 13:02 Eigenvector and Eigenvalue Applications — Topic 34 of Machine Learning Foundations 1:55:58 Building makemore Part 3: Activations & Gradients, BatchNorm 05:06 Teaching Neural Network to Solve Navier-Stokes Equations 30:57 Application 4 - Solution of PDE/ODE using Neural Networks 1:31:15 Solving differential equations with Neural Networks Similar videos 21:04 Physics-guided Learning of Neural Networks 59:03 Physics Guided Machine Learning: A New Framework for Accelerating Scientific Discovery - ISU TADS 12:51 Accelerating high-fidelity combustion simulations with classification algorithms by Wai Tong Chung 29:29 Neural ODEs for Data-Driven Reduced Order Modeling of Environmental Hydrodynamics by Sourav Dutta 58:32 Frank Noe - Advancing molecular simulation with deep learning - IPAM at UCLA More results