Conveners
Tutorial: Equivariant neural nets for physical systems
- Risi Kondor (CCM)
Tutorial: Inverse problems, sparsity and neural network priors
- Marylou Gabrie (CCM)
Tutorial: Interpretable machine learning with symbolic regression and graph networks
- Miles Cranmer (Princeton)
Tutorial: Introduction to Probabilistic Programming for Bayesian Inference with Stan
- Bob Carpenter (CCM)
Tutorial: Tensor networks and ITensor
- Miles Stoudenmire (CCQ)
Tutorial: A Mathematical Introduction to Variational Quantum Monte Carlo with Deep Neural Networks
- James Stokes (CCQ)
