AkshatKumar Nigam

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 15

Top Topics

Recent Advances

Image And Video Data

Genetic Algorithm

Top Venues

Mach. Learn. Sci. Technol.

Publications

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
Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS. CoRR (2024)
Alston Lo, Robert Pollice, AkshatKumar Nigam, Andrew D. White, Mario Krenn, Alán Aspuru-Guzik
Recent advances in the Self-Referencing Embedding Strings (SELFIES) library. CoRR (2023)
AkshatKumar Nigam, Robert Pollice, Gary Tom, Kjell Jorner, John Willes, Luca A. Thiede, Anshul Kundaje, Alán Aspuru-Guzik
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. NeurIPS (2023)
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
SELFIES and the future of molecular string representations. CoRR (2022)
AkshatKumar Nigam, Robert Pollice, Gary Tom, Kjell Jorner, Luca A. Thiede, Anshul Kundaje, Alán Aspuru-Guzik
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. CoRR (2022)
Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik
Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning. Mach. Learn. Sci. Technol. 3 (3) (2022)
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
On scientific understanding with artificial intelligence. CoRR (2022)
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
SELFIES and the future of molecular string representations. Patterns 3 (10) (2022)
AkshatKumar Nigam, Robert Pollice, Matthew F. D. Hurley, Riley J. Hickman, Matteo Aldeghi, Naruki Yoshikawa, Seyone Chithrananda, Vincent A. Voelz, Alán Aspuru-Guzik
Assigning Confidence to Molecular Property Prediction. CoRR (2021)
AkshatKumar Nigam, Robert Pollice, Alán Aspuru-Guzik
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design. CoRR (2021)
Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning. CoRR (2020)
AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. ICLR (2020)
Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik
Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation. Mach. Learn. Sci. Technol. 1 (4) (2020)
AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. CoRR (2019)
Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik
SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry. CoRR (2019)