| Name | Version | Summary | date |
| pyg-nightly |
2.7.0.dev20250725 |
Graph Neural Network Library for PyTorch |
2025-07-25 06:09:04 |
| kumoai |
2.5.1 |
AI on the Modern Data Stack |
2025-07-23 11:50:45 |
| synthetic-graph-benchmarks |
0.1.1 |
Standardized benchmarks for evaluating synthetic graph generation methods |
2025-07-23 10:31:20 |
| kumo-api |
0.25.0 |
RESTful datamodels for Kumo AI |
2025-07-17 13:33:41 |
| molgraph |
0.8.0 |
Graph Neural Networks for Molecular Machine Learning |
2025-02-11 13:40:37 |
| mlip-arena |
0.0.1a2 |
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics |
2025-01-11 18:10:02 |
| mlip_arena |
0.0.1a1 |
None |
2024-10-21 18:47:12 |
| graphmuse |
0.0.4 |
GraphMuse is a Python Library for Graph Deep Learning on Symbolic Music. |
2024-10-18 10:35:27 |
| torch-geometric |
2.6.1 |
Graph Neural Network Library for PyTorch |
2024-09-26 08:11:30 |
| torch-spatiotemporal |
0.9.5 |
A PyTorch library for spatiotemporal data processing |
2024-07-18 14:28:33 |
| aq-utilities |
2024.7.14.4 |
Data utilities for air quality data. |
2024-07-15 17:11:33 |
| lagrangebench |
0.2.0 |
LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite |
2024-07-07 23:55:24 |
| atomind-mlip |
0.0.1 |
None |
2024-03-25 06:46:06 |