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Next generation MCMC samplers with automatic differentiaion and adaptive Poisson thinning
Parallel algorithms for Metropolis Hasting Mrkov chains with Picard Map
Wraps PyTorch code in a JIT-compatible way for JAX. Supports automatically defining gradients for reverse-mode AutoDiff.
A 15TB Collection of Physics Simulation Datasets
Code repository for paper: A score-based filter for nonlinear data assimilation
Official repository for the Monte Carlo guided Diffusion for Bayesian linear inverse problems paper:
This is the Rust course used by the Android team at Google. It provides you the material to quickly teach Rust.
code for paper "Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning"
On Feynman--Kac training of partial Bayesian neural networks
Code repository for Particle Denoising Diffusion Sampler
Gradient-informed particle MCMC methods
This repository contains codes related to paper "Efficient Projection Filter Algorithm for Stochastic Dynamical Systems with Correlated Noises and State-Dependent Measurement Covariance" which can …
Posterior Sampling using Latent Diffusion - NeurIPS 2023
Custom CSS and Formatting of RISE slides
PyTorch Implementation of Diffusion Schrodinger Bridge Matching
Parallel-in-Time ODE Filters in Jax
[ICLR 2024] Controlling Vision-Language Models for Universal Image Restoration. 5th place in the NTIRE 2024 Restore Any Image Model in the Wild Challenge.
Foundations and Applications
Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Built by researchers, for research.