13 Repositories
Python pairwise-potentials Libraries
TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular potentials
TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular
Drslmarkov - Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB)
Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB) This repository provides evaluation codes of PLNLP for OGB link property prediction t
Pairwise learning neural link prediction for ogb link prediction
Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB) This repository provides evaluation codes of PLNLP for OGB link property prediction t
UF3: a python library for generating ultra-fast interatomic potentials
Ultra-Fast Force Fields (UF3) S. R. Xie, M. Rupp, and R. G. Hennig, "Ultra-fast interpretable machine-learning potentials", preprint arXiv:2110.00624
Official PyTorch implementation for paper "Efficient Two-Stage Detection of Human–Object Interactions with a Novel Unary–Pairwise Transformer"
UPT: Unary–Pairwise Transformers This repository contains the official PyTorch implementation for the paper Frederic Z. Zhang, Dylan Campbell and Step
Paper: Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identification
Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identification T M Feroz Ali, Subhasis Chaudhuri, ICVGIP-20-21
Pairwise model for commonlit competition
Pairwise model for commonlit competition To run: - install requirements - create input directory with train_folds.csv and other competition data - cd
graph-theoretic framework for robust pairwise data association
CLIPPER: A Graph-Theoretic Framework for Robust Data Association Data association is a fundamental problem in robotics and autonomy. CLIPPER provides
AllPairs is an open source test combinations generator written in Python
AllPairs is an open source test combinations generator written in Python
git《Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction》(ECCV 2020) GitHub:
Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction Code for the ECCV 2020 paper by Yiming Qian and Yasutaka Furukawa Getting
Repo for CVPR2021 paper "QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information"
QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information by Masato Tamura, Hiroki Ohashi, and Tomoaki Yosh
Multiple Pairwise Comparisons (Post Hoc) Tests in Python
scikit-posthocs is a Python package that provides post hoc tests for pairwise multiple comparisons that are usually performed in statistical data anal