Popular GitHub Repositories for Unary Potentials

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

Training neural network potentials

[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning

[CVPR'22] Official PyTorch implementation for paper "Efficient Two-Stage Detection of Human–Object Interactions with a Novel Unary–Pairwise Transformer"

SO3krates and Universal Pairwise Force Field for Molecular Simulation

[ICLR 2025 Oral] The implementation of paper "Language Representations Can be What Recommenders Need: Findings and Potentials"

python library for atomistic machine learning

Universal Joint Feature Extraction for P300 EEG Classification Using Multi-Task Autoencoder (IEEE Access)

tools for graph-based machine-learning potentials in jax

A flexible and performant framework for training machine learning potentials.

PyTorch 扩展的 API：穿孔式人工智能的穿孔反向传播

[ICML 2025 GenBio Workshop] Official Implementation for "Electrostatics from Laplacian Eigenbasis for Neural Network Interatomic Potentials"

Implementation of "Denoise Pretraining on Non-equilibrium Molecular Conformations for Accurate and Transferable Neural Potentials" in PyTorch.

SlickTok is a web app that lets you generate script for your Tiktok videos that has the potentials to go viral. If we get enough stars, we'd add more features.

This repository provides documentation for running the Active Learning workflow for fitting Gaussian Approximation Potentials.

GenAI Potentials to Enhance Medical Image Classification

Somewhat like a perceptron using unary input rather than binary

Developement code for orchestrating LLMs to do research for you. Designed for computational amorphous chemistry, using machine learning pair potentials