Self-supervised deep learning for denoising and missing wedge reconstruction of cryo-ET tomograms

Neural networks for cryo-EM reconstruction

Python API and command-line tool for Sci-Hub

Elucidating the Design Space of Diffusion-Based Generative Models (EDM)

Code for the paper Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.

Code for ICML 2023 paper, "PFGM++: Unlocking the Potential of Physics-Inspired Generative Models"

Code for NeurIPS 2022 Paper, "Poisson Flow Generative Models" (PFGM)

Code and documentation to train Stanford's Alpaca models, and generate the data.

Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement