MLMI2-CSSI/foundry
Simplifying the discovery and usage of machine-learning ready datasets in materials science and chemistry
PythonMIT
Stargazers
- Aadit-Ambadkar
- aakilchemCaelux Corp.
- abhipnVerisk, Inc
- akshay-chennaChemical Engg, IIT Delhi
- ALandauerBrown University; UW-Madison
- ancarnevaliAlistore ERI
- astrojuanlu@kedro-org
- BatmanabcdefgMars
- BraedenCuChicago
- cgrambow@Genentech
- Deathn0tParis, France
- dopplershiftUCAR/@Unidata
- drugilsbergIBM Research
- ejolly
- elensto
- felkerArgonne National Laboratory
- hgandhi2411Nurix Therapeutics | University of Rochester
- imogen-foster
- JaGeoFederal Institute for Materials Research and Testing
- jchoderaMemorial Sloan Kettering Cancer Center
- jstaLos Alamos National Laboratory
- kjappelbaumEPFL
- koushikpalnu
- longkunxulukeSamsung
- ml-evs@modl-uclouvain / @matgenix / @datalab-industries
- PanayotisManganaris
- saforem2@argonne-lcf
- salvaRCUC San Diego
- schiotzTechnical University of Denmark
- sgbaird@AccelerationConsortium (UoT) @sparks-baird (UoU)
- simonbatznerHarvard
- suan12
- TalhaKarabiyikTürkiye
- tinosulzerIonworks Technologies
- veeravignesh1Bangalore
- WardLTArgonne National Laboratory, @globus-labs