Popular GitHub Repositories for Pairwise 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

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.

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

Code for WWW'19 "Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm", which is based on LightGBM

[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

Official code for the ICML2022 paper -- GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks

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

Implementation of "Camera Relocalization by Computing Pairwise Relative Poses Using Convolutional Neural Network" by Z.Laskar et al.

Official implementation for ActFound (Nature Machine Intelligence): A bioactivity foundation model using pairwise meta-learning

Implementation, trained models and result data for the paper "Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles"

tools for graph-based machine-learning potentials in jax

We introduce the direct document relevance optimization (DDRO) for training a pairwise ranker model. DDRO encourages the model to focus on document-level relevance during generation

Feedback Forensics: An open-source toolkit to measure AI personality