[SPCL_Bcast] Towards Next-Generation Numerical Methods with Physics-Informed Neural Networks Published 2022-02-25 Download video MP4 360p Recommendations 47:08 [SPCL_Bcast] Research with AIEngine and MLIR 59:00 An Introduction to Graph Neural Networks: Models and Applications 17:38 The moment we stopped understanding AI [AlexNet] 1:12:22 [SPCL_Bcast] The digital revolution of Earth system modelling 1:13:09 Lecture 10 | Recurrent Neural Networks 21:28 Fortran is dead – Long live Fortran! 1:02:20 [SPCL_Bcast] Can I Cook a 5 o'clock Compiler Cake and Eat It at 2? 11:55:00 Best classical music. Music for the soul: Beethoven, Mozart, Schubert, Chopin, Bach ... 🎶🎶 1:04:58 TILOS Seminar: What Kinds of Functions do Neural Networks Learn? Theory and Practical Applications 15:50 Compressing Multidimensional Weather and Climate Data Into Neural Networks 08:29 Google Data Center 360° Tour Similar videos 1:00:45 Physics-Informed Machine Learning: Blending data and physics for fast predictions 1:02:53 DDPS | Scientific Machine Learning through the Lens of Physics-Informed Neural Networks 41:34 PDENA22: Physics-informed Neural Networks: A new paradigm for learning physical laws 1:01:38 [SPCL_Bcast] Transferable Deep Learning Surrogates for Solving PDEs 58:10 Parallel Physics-informed Neural Networks via Domain Decomposition 00:11 Aspirants practicing eatingetiquette # SSB #SSBPreparation #NDA #CDS #Defence #DefenceAcademy 52:26 Polariton neural networks | Prof. Michał Matuszewski 35:11 Is the Future of Linear Algebra.. Random? 1:21:24 SPINN -- an interpretable sparse NN architecture for PDEs 43:34 Weinan E: "High Dimensional PDEs: Theory and Numerical Algorithms" More results