| Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation M Krenn, F Hase, AK Nigam, P Friederich, A Aspuru-Guzik Machine Learning: Science and Technology, 2020 | 82* | 2020 |
| Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space AK Nigam, P Friederich, M Krenn, A Aspuru-Guzik International Conference on Learning Representations (ICLR)., 2020 | 33 | 2020 |
| Data-driven strategies for accelerated materials design R Pollice, G dos Passos Gomes, M Aldeghi, RJ Hickman, M Krenn, ... Accounts of Chemical Research 54 (4), 849-860, 2021 | 10 | 2021 |
| Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIES AK Nigam, R Pollice, M Krenn, G dos Passos Gomes, A Aspuru-Guzik Chemical Science, 2021 | 8 | 2021 |
| A comprehensive discovery platform for organophosphorus ligands for catalysis T Gensch, G dos Passos Gomes, P Friederich, E Peters, T Gaudin, ... ChemRxiv, 2021 | 2 | 2021 |
| Assigning Confidence to Molecular Property Prediction AK Nigam, R Pollice, MFD Hurley, RJ Hickman, M Aldeghi, N Yoshikawa, ... arXiv preprint arXiv:2102.11439, 2021 | 2 | 2021 |
| Exploring the chemical space without bias: data-free molecule generation with DQN and SELFIES T Gaudin, AK Nigam, A Aspuru-Guzik NeurIPS-2019 MLPS Workshop, 0 | 2 | |
| Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning LA Thiede, M Krenn, AK Nigam, A Aspuru-Guzik NeurIPS 2019, Second Workshop on Machine Learning and the Physical Sciences, 2020 | 1 | 2020 |
| JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design AK Nigam, R Pollice, A Aspuru-Guzik arXiv preprint arXiv:2106.04011, 2021 | | 2021 |
Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Verified email at utoronto.ca
