AkshatKumar Nigam

15 papers A* 2Journal 13
YearRankTypeTitle / Venue / Authors
2024 J jnl
Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS.
CoRR
Mohammad Ghazi Vakili, Christoph Gorgulla, AkshatKumar Nigam, Dmitry Bezrukov, Daniel Varoli, Alex Aliper, Daniil Polykovskiy, Krishna M. Padmanabha Das, Jamie Snider, Anna Lyakisheva, Ardalan Hosseini Mansob, Zhong Yao, Lela Bitar, Eugene Radchenko, Xiao Ding, Jinxin Liu, Fanye Meng, Feng Ren, Yudong Cao, Igor Stagljar, Alán Aspuru-Guzik, Alex Zhavoronkov
2023 J jnl
Recent advances in the Self-Referencing Embedding Strings (SELFIES) library.
CoRR
Alston Lo, Robert Pollice, AkshatKumar Nigam, Andrew D. White, Mario Krenn, Alán Aspuru-Guzik
2023 A* conf
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design.
NeurIPS
AkshatKumar Nigam, Robert Pollice, Gary Tom, Kjell Jorner, John Willes, Luca A. Thiede, Anshul Kundaje, Alán Aspuru-Guzik
2022 J jnl
Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning.
Mach. Learn. Sci. Technol.
Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik
2022 J jnl
On scientific understanding with artificial intelligence.
CoRR
Mario Krenn, Robert Pollice, Si Yue Guo, Matteo Aldeghi, Alba Cervera-Lierta, Pascal Friederich, Gabriel dos Passos Gomes, Florian Häse, Adrian Jinich, AkshatKumar Nigam, Zhenpeng Yao, Alán Aspuru-Guzik
2022 J jnl
SELFIES and the future of molecular string representations.
CoRR
Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik
2022 J jnl
SELFIES and the future of molecular string representations.
Patterns
Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik
2022 J jnl
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design.
CoRR
AkshatKumar Nigam, Robert Pollice, Gary Tom, Kjell Jorner, Luca A. Thiede, Anshul Kundaje, Alán Aspuru-Guzik
2021 J jnl
Assigning Confidence to Molecular Property Prediction.
CoRR
AkshatKumar Nigam, Robert Pollice, Matthew F. D. Hurley, Riley J. Hickman, Matteo Aldeghi, Naruki Yoshikawa, Seyone Chithrananda, Vincent A. Voelz, Alán Aspuru-Guzik
2021 J jnl
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design.
CoRR
AkshatKumar Nigam, Robert Pollice, Alán Aspuru-Guzik
2020 A* conf
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space.
ICLR
AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
2020 J jnl
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning.
CoRR
Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik
2020 J jnl
Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation.
Mach. Learn. Sci. Technol.
Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik
2019 J jnl
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space.
CoRR
AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
2019 J jnl
SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry.
CoRR
Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik