KZiemian
commented
2 years ago JuliaCon 2020 | Keynote: Scientific Machine Learning | Prof Karen Willcox, https://www.youtube.com/watch?v=Bk4PJnjuPps
It was quite a challenge, but here is my attempt at making timestamps to this lecture. You can change anything, especially my bad English, if you want.
00:00 Welcome and information about JuliaCon 2020 01:42 Introduction and acknowledgments 02:50 Outline of the talk 03:25 What is Scientific Machine Learning (SciML)? 05:04 What are the opportunities and challenges of SciML? 10:32 BIG DATA alone is not enough 11:27 Using physics base models means that we are doing Computational Science 13:19 Problem 1: Complex multiscale multiphysics phenomena 14:46 Problem 2: High dimensional parameters 15:54 Problem 3: Data are sparse, intrusive and expensive to acquire 16:48 Problem 4: Rare events 17:33 Problem 5: Uncertainty qualification 18:11 SciML and Computational Science, summary 18:47 Example: flow inside a rocket engine combustor 20:08 Example: equations of flow inside a rocket engine combustor 20:41 Physics-based model are powerful but computational expensive 23:10 Overview of model reduction methods 26:04 Similarities and differences between model reduction and ML 27:17 Can we have best of two words (model reduction and ML)? 30:05 Overview of Lift & Learn approach 33:00 Example: Lift & Learn approach to 2D flow in a rocket engine 34:34 Example: Training of the model 36:04 Example: Comparing results for pressure and temperature 37:38 Outlook of Sci ML 38:42 Diverse future of computational science and programming languages 39:31 Q&A: Advice for people bringing ML approach to scientific problems 42:09 Q&A: Pitfalls of interplay between domains knowledge and ML 43:33 Q&A: Does presented approach improves fidelity of solution of highly non-linear systems?
logankilpatrick
JuliaCon 2020 | Keynote: Scientific Machine Learning | Prof Karen Willcox, https://www.youtube.com/watch?v=Bk4PJnjuPps
I will try to make timestamps to this video to the end of the week. I'm not promise anything, since this video, which I like and already watch it twice, can be too hard to me to grasp enough to to make desired timestamps.