Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Koziarski Michał"'
Autor:
Boussif, Oussama, Ezzine, Léna Néhale, Viviano, Joseph D, Koziarski, Michał, Jain, Moksh, Malkin, Nikolay, Bengio, Emmanuel, Assouel, Rim, Bengio, Yoshua
As trajectories sampled by policies used by reinforcement learning (RL) and generative flow networks (GFlowNets) grow longer, credit assignment and exploration become more challenging, and the long planning horizon hinders mode discovery and generali
Externí odkaz:
http://arxiv.org/abs/2410.15184
Autor:
Lu, Stephen Zhewen, Lu, Ziqing, Hajiramezanali, Ehsan, Biancalani, Tommaso, Bengio, Yoshua, Scalia, Gabriele, Koziarski, Michał
High-content phenotypic screening, including high-content imaging (HCI), has gained popularity in the last few years for its ability to characterize novel therapeutics without prior knowledge of the protein target. When combined with deep learning te
Externí odkaz:
http://arxiv.org/abs/2408.05196
Autor:
Gaiński, Piotr, Koziarski, Michał, Maziarz, Krzysztof, Segler, Marwin, Tabor, Jacek, Śmieja, Marek
Single-step retrosynthesis aims to predict a set of reactions that lead to the creation of a target molecule, which is a crucial task in molecular discovery. Although a target molecule can often be synthesized with multiple different reactions, it is
Externí odkaz:
http://arxiv.org/abs/2406.18739
Autor:
Koziarski, Michał, Rekesh, Andrei, Shevchuk, Dmytro, van der Sloot, Almer, Gaiński, Piotr, Bengio, Yoshua, Liu, Cheng-Hao, Tyers, Mike, Batey, Robert A.
Generative models hold great promise for small molecule discovery, significantly increasing the size of search space compared to traditional in silico screening libraries. However, most existing machine learning methods for small molecule generation
Externí odkaz:
http://arxiv.org/abs/2406.08506
Autor:
Koziarski Michał, Cyganek Bogusław
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 28, Iss 4, Pp 735-744 (2018)
Due to the advances made in recent years, methods based on deep neural networks have been able to achieve a state-of-the-art performance in various computer vision problems. In some tasks, such as image recognition, neural-based approaches have even
Externí odkaz:
https://doaj.org/article/ed95638243734d8bb2358feafbbc2c4f
Autor:
Koziarski, Michał, Abukalam, Mohammed, Shah, Vedant, Vaillancourt, Louis, Schuetz, Doris Alexandra, Jain, Moksh, van der Sloot, Almer, Bourgey, Mathieu, Marinier, Anne, Bengio, Yoshua
DNA-encoded libraries (DELs) are a powerful approach for rapidly screening large numbers of diverse compounds. One of the key challenges in using DELs is library design, which involves choosing the building blocks that will be combinatorially combine
Externí odkaz:
http://arxiv.org/abs/2404.10094
Autor:
Koziarski Michał, Wożniak Michał
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 27, Iss 4, Pp 727-736 (2017)
Imbalanced data classification is one of the most widespread challenges in contemporary pattern recognition. Varying levels of imbalance may be observed in most real datasets, affecting the performance of classification algorithms. Particularly, high
Externí odkaz:
https://doaj.org/article/ce85efaead2b40ffa1bbd0cf7f47e396
Autor:
Volokhova, Alexandra, Koziarski, Michał, Hernández-García, Alex, Liu, Cheng-Hao, Miret, Santiago, Lemos, Pablo, Thiede, Luca, Yan, Zichao, Aspuru-Guzik, Alán, Bengio, Yoshua
Sampling diverse, thermodynamically feasible molecular conformations plays a crucial role in predicting properties of a molecule. In this paper we propose to use GFlowNet for sampling conformations of small molecules from the Boltzmann distribution,
Externí odkaz:
http://arxiv.org/abs/2310.14782
Autor:
AI4Science, Mila, Hernandez-Garcia, Alex, Duval, Alexandre, Volokhova, Alexandra, Bengio, Yoshua, Sharma, Divya, Carrier, Pierre Luc, Benabed, Yasmine, Koziarski, Michał, Schmidt, Victor
Accelerating material discovery holds the potential to greatly help mitigate the climate crisis. Discovering new solid-state materials such as electrocatalysts, super-ionic conductors or photovoltaic materials can have a crucial impact, for instance,
Externí odkaz:
http://arxiv.org/abs/2310.04925
Autor:
Beaini, Dominique, Huang, Shenyang, Cunha, Joao Alex, Li, Zhiyi, Moisescu-Pareja, Gabriela, Dymov, Oleksandr, Maddrell-Mander, Samuel, McLean, Callum, Wenkel, Frederik, Müller, Luis, Mohamud, Jama Hussein, Parviz, Ali, Craig, Michael, Koziarski, Michał, Lu, Jiarui, Zhu, Zhaocheng, Gabellini, Cristian, Klaser, Kerstin, Dean, Josef, Wognum, Cas, Sypetkowski, Maciej, Rabusseau, Guillaume, Rabbany, Reihaneh, Tang, Jian, Morris, Christopher, Koutis, Ioannis, Ravanelli, Mirco, Wolf, Guy, Tossou, Prudencio, Mary, Hadrien, Bois, Therence, Fitzgibbon, Andrew, Banaszewski, Błażej, Martin, Chad, Masters, Dominic
Recently, pre-trained foundation models have enabled significant advancements in multiple fields. In molecular machine learning, however, where datasets are often hand-curated, and hence typically small, the lack of datasets with labeled features, an
Externí odkaz:
http://arxiv.org/abs/2310.04292