Gaiński, Piotr

9 publications

NeurIPS 2025 Scalable and Cost-Efficient De Novo Template-Based Molecular Generation Piotr Gaiński, Oussama Boussif, Andrei Rekesh, Dmytro Shevchuk, Ali Parviz, Mike Tyers, Robert A. Batey, Michał Koziarski

ICLRW 2025 Scalable and Cost-Efficient De Novo Template-Based Molecular Generation Piotr Gaiński, Oussama Boussif, Dmytro Shevchuk, Andrei Rekesh, Ali Parviz, Mike Tyers, Robert A. Batey, Michał Koziarski

NeurIPS 2024 RGFN: Synthesizable Molecular Generation Using GFlowNets Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey

ICMLW 2024 RGFN: Synthesizable Molecular Generation Using GFlowNets Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer M. van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey

ICLRW 2024 Re-Evaluating Retrosynthesis Algorithms with Syntheseus Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler

ICLRW 2024 RetroGFN: Diverse and Feasible Retrosynthesis Using GFlowNets Piotr Gaiński, Michał Koziarski, Krzysztof Maziarz, Marwin Segler, Jacek Tabor, Marek Śmieja

ECML-PKDD 2023 ChiENN: Embracing Molecular Chirality with Graph Neural Networks Piotr Gainski, Michal Koziarski, Jacek Tabor, Marek Smieja

NeurIPSW 2023 Re-Evaluating Retrosynthesis Algorithms with Syntheseus Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler

AAAI 2022 HuggingMolecules: An Open-Source Library for Transformer-Based Molecular Property Prediction (Student Abstract) Piotr Gainski, Lukasz Maziarka, Tomasz Danel, Stanislaw Jastrzebski