Dataset licenses and attribution
The GenBench software is MIT-licensed, but that license does not apply to third-party datasets. Each stored dataset retains its upstream license. The prepared files are adaptations: GenBench verifies the upstream release, then performs the deterministic splitting, normalization, packing, or feature selection described in that benchmark's metadata and preparation module.
Publicly redistributed prepared data
| Directory | Source and attribution | License |
|---|---|---|
QM9 |
Ramakrishnan, Dral, Rupp, and von Lilienfeld, Data for 133885 GDB-9 molecules, including Figshare files 3195389 and 3195404 | CC0 1.0 |
DeepSTARR |
Bernardo P. de Almeida, DeepSTARR manuscript data | CC BY 4.0 |
JetNet30 |
Raghav Kansal, Javier Duarte, Su Hao, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, and Dimitrios Gunopulos, JetNet | CC BY 4.0 |
MiniBooNE |
Byron Roe, MiniBooNE particle identification, UCI Machine Learning Repository | CC BY 4.0 |
NavierStokes |
NeuralOperator Team, Navier-Stokes Dataset | CC BY 4.0 |
GuacaMol |
BenevolentAI, GuacaMol standardized ChEMBL distribution-learning split; underlying records from ChEMBL | CC BY-SA 3.0 |
SpeechCommands |
Pete Warden and the TensorFlow/AIY teams, Speech Commands V2 | CC BY 4.0 |
Source-only datasets
GenBench does not redistribute the following data. The repository contains checksum-verified Python preparation code that downloads each release directly from its original host for a user's own use.
| Dataset | Why it is source-only |
|---|---|
| CIFAR-10 | The official release specifies no dataset license or redistribution grant. |
| MNIST | The official distribution and the CVDF mirror specify no general redistribution license. |
This file records upstream terms for reproducibility and is not legal advice.