Curvlearn, a Tensorflow based non-Euclidean deep learning framework.

📚 华章数学丛书高清扫描

Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

An E(3) equivariant Graph Neural Network for predicting electronic Hamiltonian matrix

Technical software application for creating tight-binding Hamiltonian from DFT results

band plot using python matplotlib

Reinforcement learning (RL) implementation of imperfect information game Mahjong using markov decision processes to predict future game states

Official implementation for 'Sparse denoising diffusion for large graph generation'

Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

Generative modeling of molecular dynamics trajectories

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

Official PyTorch Implementation of "SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers"

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

code for "Riemannian Flow Matching on General Geometries".

A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.

The official implementation of "[MASK] is All You Need"

ProtMamba: a homology-aware but alignment-free protein state space model

Riemannian Adaptive Optimization Methods with pytorch optim

nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset

Artificial Intelligence Research for Science (AIRS)

AlphaFold 3 inference pipeline.

Deep neural networks for density functional theory Hamiltonian.

Code for “FlowMM Generating Materials with Riemannian Flow Matching” and "FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions"

Mamba SSM architecture

剑桥雅思