Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening von Wu, Nan, Phang, Jason, Park, Jungkyu, Shen, Yiqiu, Huang, Zhe, Zorin, Masha, Jastrzebski, Stanislaw, Fevry, Thibault, Katsnelson, Joe, Kim, Eric, Wolfson, Stacey, Parikh, Ujas, Gaddam, Sushma, Lin, Leng Leng Young, Ho, Kara, Weinstein, Joshua D., Reig, Beatriu, Gao, Yiming, Toth, Hildegard, Pysarenko, Kristine, Lewin, Alana, Lee, Jiyon, Airola, Krystal, Mema, Eralda, Chung, Stephanie, Hwang, Esther, Samreen, Naziya, Kim, S. Gene, Heacock, Laura, Moy, Linda, Cho, Kyunghyun, Geras, Krzysztof J.

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Generative Models Should at Least Be Able to Design Molecules That Dock Well: A New Benchmark von Ciepliński, Tobiasz, Danel, Tomasz, Podlewska, Sabina, Jastrzȩbski, Stanisław

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Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits von Sacha, Mikołaj, Błaż, Mikołaj, Byrski, Piotr, Dąbrowski-Tumański, Paweł, Chromiński, Mikołaj, Loska, Rafał, Włodarczyk-Pruszyński, Paweł, Jastrzębski, Stanisław

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RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software von Liu, Cheng-Hao, Korablyov, Maksym, Jastrzębski, Stanisław, Włodarczyk-Pruszyński, Paweł, Bengio, Yoshua, Segler, Marwin

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Cramer-Wold Auto-Encoder von Knop, Szymon, Spurek, Przemyslaw, Tabor, Jacek, Podolak, Igor, Mazur, Marcin, Jastrzebski, Stanislaw

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Development of New Methods Needs Proper EvaluationBenchmarking Sets for Machine Learning Experiments for Class A GPCRs von Leśniak, Damian, Podlewska, Sabina, Jastrzębski, Stanisław, Sieradzki, Igor, Bojarski, Andrzej J, Tabor, Jacek

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Relative molecule self-attention transformer von Maziarka, Łukasz, Majchrowski, Dawid, Danel, Tomasz, Gaiński, Piotr, Tabor, Jacek, Podolak, Igor, Morkisz, Paweł, Jastrzębski, Stanisław

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Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening von Jastrzębski, Stanisław, Szymczak, Maciej, Pocha, Agnieszka, Mordalski, Stefan, Tabor, Jacek, Bojarski, Andrzej J, Podlewska, Sabina

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Quo vadis G protein-coupled receptor ligands? A tool for analysis of the emergence of new groups of compounds over time von Leśniak, Damian, Jastrzębski, Stanisław, Podlewska, Sabina, Czarnecki, Wojciech M., Bojarski, Andrzej J.

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Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio von Jastrzębski, Stanislaw, Kenton, Zachary, Arpit, Devansh, Ballas, Nicolas, Fischer, Asja, Bengio, Yoshua, Storkey, Amos

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An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department von Shamout, Farah E., Shen, Yiqiu, Wu, Nan, Kaku, Aakash, Park, Jungkyu, Makino, Taro, Jastrzębski, Stanisław, Witowski, Jan, Wang, Duo, Zhang, Ben, Dogra, Siddhant, Cao, Meng, Razavian, Narges, Kudlowitz, David, Azour, Lea, Moore, William, Lui, Yvonne W., Aphinyanaphongs, Yindalon, Fernandez-Granda, Carlos, Geras, Krzysztof J.

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Differences between human and machine perception in medical diagnosis von Makino, Taro, Jastrzębski, Stanisław, Oleszkiewicz, Witold, Chacko, Celin, Ehrenpreis, Robin, Samreen, Naziya, Chhor, Chloe, Kim, Eric, Lee, Jiyon, Pysarenko, Kristine, Reig, Beatriu, Toth, Hildegard, Awal, Divya, Du, Linda, Kim, Alice, Park, James, Sodickson, Daniel K., Heacock, Laura, Moy, Linda, Cho, Kyunghyun, Geras, Krzysztof J.

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An efficient deep neural network to classify large 3D images with small objects von Park, Jungkyu, Chledowski, Jakub, Jastrzebski, Stanislaw, Witowski, Jan, Xu, Yanqi, Du, Linda, Gaddam, Sushma, Kim, Eric, Lewin, Alana, Parikh, Ujas, Plaunova, Anastasia, Chen, Sardius, Millet, Alexandra, Park, James, Pysarenko, Kristine, Patel, Shalin, Goldberg, Julia, Wegener, Melanie, Moy, Linda, Heacock, Laura, Reig, Beatriu, Geras, Krzysztof J.

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Large Scale Structure of Neural Network Loss Landscapes von Fort, Stanislav, Jastrzebski, Stanislaw

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We Should at Least Be Able to Design Molecules That Dock Well von Tobiasz Cieplinski, Danel, Tomasz, Podlewska, Sabina, Jastrzebski, Stanislaw

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Osprey: Hyperparameter Optimization for Machine Learning von T. McGibbon, Robert, X. Hernández, Carlos, P. Harrigan, Matthew, Kearnes, Steven, M. Sultan, Mohammad, Jastrzebski, Stanislaw, E. Husic, Brooke, S. Pande, Vijay

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Large Scale Structure of Neural Network Loss Landscapes von t, Stanislav, Jastrzebski, Stanislaw

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Stiffness: A New Perspective on Generalization in Neural Networks von Fort, Stanislav, Nowak, Paweł Krzysztof, Jastrzebski, Stanislaw, Narayanan, Srini

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Generative Active Learning for the Search of Small-molecule Protein Binders von Korablyov, Maksym, Liu, Cheng-Hao, Jain, Moksh, van der Sloot, Almer M, Jolicoeur, Eric, Ruediger, Edward, Nica, Andrei Cristian, Bengio, Emmanuel, Lapchevskyi, Kostiantyn, St-Cyr, Daniel, Schuetz, Doris Alexandra, Butoi, Victor Ion, Rector-Brooks, Jarrid, Blackburn, Simon, Feng, Leo, Nekoei, Hadi, Gottipati, SaiKrishna, Vijayan, Priyesh, Gupta, Prateek, Rampášek, Ladislav, Avancha, Sasikanth, Bacon, Pierre-Luc, Hamilton, William L, Paige, Brooks, Misra, Sanchit, Jastrzebski, Stanislaw Kamil, Kaul, Bharat, Precup, Doina, Hernández-Lobato, José Miguel, Segler, Marwin, Bronstein, Michael, Marinier, Anne, Tyers, Mike, Bengio, Yoshua

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The Break-Even Point on Optimization Trajectories of Deep Neural Networks von Jastrzebski, Stanislaw, Szymczak, Maciej, Fort, Stanislav, Arpit, Devansh, Tabor, Jacek, Cho, Kyunghyun, Geras, Krzysztof

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