Schoenholz, Samuel S.

Scaling deep learning for materials discovery

Merchant, A., Batzner, S., Schoenholz, S. S., Aykol, M., Cheon, G., & Cubuk, E. D. (2023) · Nature

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 1,527

Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error

Faber, F. A., Hutchison, L., Huang, B., Gilmer, J., Schoenholz, S. S., Dahl, G. E., Vinyals, O., Kearnes, S., Riley, P. F., & von Lilienfeld, O. A. (2017) · Journal of Chemical Theory and Computation

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 651

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569