Introduction to Probabilistic Programming for Bayesian Inference with Stan

Advanced MCMC methods

Hierarchical low rank compression and an application in many-body quantum physics

Equivariant neural nets for physical systems

Recurrent VAE for anomaly detection in supernova time series

Differentiable programming for protein structure alignment

A Mathematical Introduction to Variational Quantum Monte Carlo with Deep Neural Networks

Inverse problems, sparsity and neural network priors

Descartes versus bayes: Views of deep net theories

SARS-CoV-2 transmission in Marine recruits during quarantine and training

Interpretable machine learning with symbolic regression and graph networks

Discovering symbolic models in physical systems using deep learning

An automated framework for efficiently designing deep convolutional neural networks in genomics

Tensor networks and ITensor