Nicolas Boulle: Elliptic PDE learning is provably data-efficient
1:46:22
Nathan Doumèche: Physics-Informed Machine Learning as a Kernel Method
57:13
Florian Schaefer: Statistical Inference and PDEs: From operator learning to shock capturing
27:14
Transformers (how LLMs work) explained visually | DL5
58:47
Dr. Tristan Bereau (Heidelberg) - Free-energy Calculations from Neural Thermodynamic Integration
1:03:14
Lorenz Richter: An Optimal Control Perspective on Diffusion-Based Generative Modeling
11:48
'My jaw is dropped': Canadian official's interview stuns Amanpour
1:11:58
Petar Veličković: Graph Deep Learning: Monoids and time, Embracing asynchrony in (G)NNs
26:52