physics-informed neural network for elastodynamics problem

TorchDR - PyTorch Dimensionality Reduction

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

Investigating PINNs

A differentiable PDE solving framework for machine learning

Physics-informed learning of governing equations from scarce data

PDEBench: An Extensive Benchmark for Scientific Machine Learning

A benchmark for the next generation of data-driven global weather models.

Aligning protein generative models with experimental fitness

Easy generative modeling in PyTorch.

pyOptSparse is an object-oriented framework for formulating and solving nonlinear constrained optimization problems in an efficient, reusable, and portable manner.

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Comparison between GFlowNets & Maximum Entropy RL

Normalizing flows in PyTorch. Current intended use is education not production.

A summary of related works about flow matching, stochastic interpolants

El0ps: An Exact L0-Problem Solver

Implementation of a discord channel scraper to generate datasets.

A linear estimator on top of clip to predict the aesthetic quality of pictures

Make your tweets more punchy with Mixtral and GPT

Frank-Wolfe optimization variants with a linear convergence rate

Suno AI's Bark model in C/C for fast text-to-speech

A collection of typst templates

PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator (NeurIPS 2024)

Experimental Nintendo Switch Emulator written in C#

FoldFlow: SE(3)-Stochastic Flow Matching for Protein Backbone Generation