We aim to broadly disseminate our results. Overall, our goal is that this project creates new paradigms of practice for the next generation of computational scientists.

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Tim Kralj

Aditya Nandy, Chenru Duan, Michael G. Taylor, Fang Liu, Adam H. Steeves, and Heather J. Kulik. “Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning.” Chemical Reviews, 2021.

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William Moses, Valentin Churavy. “Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients.” In Advances in Neural Information Processing Systems 33 (NeurIPS 2020).

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