DIVE Lab, Texas A&M University

DIG

A library for graph deep learning research

AIRS

Artificial Intelligence Research for Science (AIRS)

GOOD

GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]

MoleculeX

GraphBP

Official implementation of "Generating 3D Molecules for Target Protein Binding" [ICML2022 Long Presentation]

DeeperGNN

Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]

Noise2Same

Sys2Bench

Sys2Bench is a benchmarking suite designed to evaluate reasoning and planning capabilities of large language models across algorithmic, logical, arithmetic, and common-sense reasoning tasks.

ATTA

Active Test-Time Adaptation: Theoretical Analyses and An Algorithm [ICLR 2024]

Non-Local-GNN

Official implementation of "Non-Local Graph Neural Networks" [TPAMI]

LECI

The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS 2023)

LGLP

MFA

Official code repository of paper Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency.

DIG_storage

Save data or other files for DIG library usage

GVTNets

Global Voxel Transformer Networks (GVTNets)

Neighbor2Seq

Official implementation of "Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences" [SDM2022]

RMwGGIS

Official implementation of "Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models" [ICLR2023]

DSearch

AEANets

AEANets

E2H-Reasoning

Implementation of "Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning"

ForgetNet

wsdmcup2022

wsdmcup2022

DGML-master

divelab

DrugOOD

OOD Dataset Curator and Benchmark for AI-aided Drug Discovery

E2H

MoleculeKit

IFL-DIF

Invariant function learning for ODEs: Disentanglement of Invariant Functions. The implementation of "Discovering Physics Laws of Dynamical Systems via Invariant Function Learning" (ICML 2025)

OpenRLHF

An Easy-to-use, Scalable and High-performance RLHF Framework based on Ray (PPO & GRPO & REINFORCE++ & vLLM & Ray & Dynamic Sampling & Async Agentic RL)

VIDD