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ORCIDStanislaw Jastrzebski
Stanislaw K. Jastrzebski – Stanislaw Kamil Jastrzebski – Stanisław Jastrzębski
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- unicode name: Stanisław Jastrzębski
- affiliation: Jagiellonian University, Cracow, Poland
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2020 – today
- 2024
[j11]Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski:
Relative molecule self-attention transformer. J. Cheminformatics 16(1): 3 (2024)- [j10]Jungkyu Park
, Jakub Chledowski, Stanislaw Jastrzebski, Jan Witowski, Yanqi Xu, Linda Du, Sushma Gaddam, Eric Kim, Alana Lewin, Ujas Parikh, Anastasia Plaunova, Sardius Chen, Alexandra Millet, James Park, Kristine Pysarenko, Shalin Patel, Julia Goldberg, Melanie Wegener, Linda Moy, Laura Heacock, Beatriu Reig, Krzysztof J. Geras:
An Efficient Deep Neural Network to Classify Large 3D Images With Small Objects. IEEE Trans. Medical Imaging 43(1): 351-365 (2024) - [i31]Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio:
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR abs/2405.01616 (2024) - 2023
- [j9]Tobiasz Cieplinski, Tomasz Danel, Sabina Podlewska, Stanislaw Jastrzebski:
Generative Models Should at Least Be Able to Design Molecules That Dock Well: A New Benchmark. J. Chem. Inf. Model. 63(11): 3238-3247 (2023) - [i30]Mikolaj Sacha, Michal Sadowski, Piotr Kozakowski, Ruard van Workum, Stanislaw Jastrzebski:
Molecule-Edit Templates for Efficient and Accurate Retrosynthesis Prediction. CoRR abs/2310.07313 (2023) - 2022
- [j8]Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler:
RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software. J. Chem. Inf. Model. 62(10): 2293-2300 (2022) - [c16]Piotr Gainski, Lukasz Maziarka, Tomasz Danel, Stanislaw Jastrzebski:
HuggingMolecules: An Open-Source Library for Transformer-Based Molecular Property Prediction (Student Abstract). AAAI 2022: 12949-12950 - [c15]Nan Wu, Stanislaw Jastrzebski, Kyunghyun Cho, Krzysztof J. Geras:
Characterizing and Overcoming the Greedy Nature of Learning in Multi-modal Deep Neural Networks. ICML 2022: 24043-24055 - [i29]Nan Wu, Stanislaw Jastrzebski, Kyunghyun Cho, Krzysztof J. Geras:
Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks. CoRR abs/2202.05306 (2022) - [i28]Jungkyu Park, Jakub Chledowski, Stanislaw Jastrzebski, Jan Witowski, Yanqi Xu, Linda Du, Sushma Gaddam, Eric Kim, Alana Lewin, Ujas Parikh, Anastasia Plaunova, Sardius Chen, Alexandra Millet, James Park, Kristine Pysarenko, Shalin Patel, Julia Goldberg, Melanie Wegener, Linda Moy, Laura Heacock, Beatriu Reig, Krzysztof J. Geras:
3D-GMIC: an efficient deep neural network to find small objects in large 3D images. CoRR abs/2210.08645 (2022) - 2021
- [j7]Mikolaj Sacha, Mikolaj Blaz, Piotr Byrski, Pawel Dabrowski-Tumanski, Mikolaj Chrominski, Rafal Loska, Pawel Wlodarczyk-Pruszynski, Stanislaw Jastrzebski:
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits. J. Chem. Inf. Model. 61(7): 3273-3284 (2021) - [j6]Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras:
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. npj Digit. Medicine 4 (2021) - [c14]Stanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J. Geras:
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization. ICML 2021: 4772-4784 - [i27]Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski:
Relative Molecule Self-Attention Transformer. CoRR abs/2110.05841 (2021) - 2020
- [j5]Stanislaw Jastrzebski, Maciej Szymczak, Agnieszka Pocha, Stefan Mordalski, Jacek Tabor, Andrzej J. Bojarski, Sabina Podlewska:
Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening. J. Chem. Inf. Model. 60(9): 4246-4262 (2020) - [j4]Szymon Knop, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski:
Cramer-Wold Auto-Encoder. J. Mach. Learn. Res. 21: 164:1-164:28 (2020) - [j3]Nan Wu, Jason Phang, Jungkyu Park, Yiqiu Shen, Zhe Huang, Masha Zorin, Stanislaw Jastrzebski, Thibault Févry, Joe Katsnelson, Eric Kim, Stacey Wolfson, Ujas Parikh, Sushma Gaddam, Leng Leng Young Lin, Kara Ho, Joshua D. Weinstein, Beatriu Reig, Yiming Gao, Hildegard Toth, Kristine Pysarenko, Alana Lewin, Jiyon Lee, Krystal Airola, Eralda Mema, Stephanie Chung, Esther Hwang, Naziya Samreen, Sungheon Gene Kim, Laura Heacock, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras:
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening. IEEE Trans. Medical Imaging 39(4): 1184-1194 (2020) - [c13]Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras:
The Break-Even Point on Optimization Trajectories of Deep Neural Networks. ICLR 2020 - [c12]Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor, Lukasz Maziarka, Stanislaw Jastrzebski:
Non-linear ICA Based on Cramer-Wold Metric. ICONIP (3) 2020: 294-305 - [c11]Nan Wu, Stanislaw Jastrzebski, Jungkyu Park, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras:
Improving the Ability of Deep Neural Networks to Use Information from Multiple Views in Breast Cancer Screening. MIDL 2020: 827-842 - [i26]Lukasz Maziarka, Tomasz Danel, Slawomir Mucha, Krzysztof Rataj, Jacek Tabor, Stanislaw Jastrzebski:
Molecule Attention Transformer. CoRR abs/2002.08264 (2020) - [i25]Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras:
The Break-Even Point on Optimization Trajectories of Deep Neural Networks. CoRR abs/2002.09572 (2020) - [i24]Witold Oleszkiewicz, Taro Makino, Stanislaw Jastrzebski, Tomasz Trzcinski, Linda Moy, Kyunghyun Cho, Laura Heacock, Krzysztof J. Geras:
Understanding the robustness of deep neural network classifiers for breast cancer screening. CoRR abs/2003.10041 (2020) - [i23]Mikolaj Sacha, Mikolaj Blaz, Piotr Byrski, Pawel Wlodarczyk-Pruszynski, Stanislaw Jastrzebski:
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits. CoRR abs/2006.15426 (2020) - [i22]Tobiasz Cieplinski, Tomasz Danel, Sabina Podlewska, Stanislaw Jastrzebski:
We should at least be able to Design Molecules that Dock Well. CoRR abs/2006.16955 (2020) - [i21]Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras:
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. CoRR abs/2008.01774 (2020) - [i20]Luke Nicholas Darlow, Stanislaw Jastrzebski, Amos J. Storkey:
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks. CoRR abs/2011.11486 (2020) - [i19]Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler:
RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design. CoRR abs/2011.13042 (2020) - [i18]Taro Makino, Stanislaw Jastrzebski, Witold Oleszkiewicz, Celin Chacko, Robin Ehrenpreis, Naziya Samreen, Chloe Chhor, Eric Kim, Jiyon Lee, Kristine Pysarenko, Beatriu Reig, Hildegard Toth, Divya Awal, Linda Du, Alice Kim, James Park, Daniel K. Sodickson, Laura Heacock, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras:
Differences between human and machine perception in medical diagnosis. CoRR abs/2011.14036 (2020) - [i17]Stanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J. Geras:
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization. CoRR abs/2012.14193 (2020)
2010 – 2019
- 2019
- [j2]Damian Lesniak, Sabina Podlewska, Stanislaw Jastrzebski, Igor Sieradzki, Andrzej J. Bojarski, Jacek Tabor:
Development of New Methods Needs Proper Evaluation - Benchmarking Sets for Machine Learning Experiments for Class A GPCRs. J. Chem. Inf. Model. 59(12): 4974-4992 (2019) - [c10]Wojciech Tarnowski, Piotr Warchol, Stanislaw Jastrzebski, Jacek Tabor, Maciej A. Nowak:
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function. AISTATS 2019: 2221-2230 - [c9]Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. ICLR (Poster) 2019 - [c8]Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, Sylvain Gelly:
Parameter-Efficient Transfer Learning for NLP. ICML 2019: 2790-2799 - [c7]Stanislav Fort, Stanislaw Jastrzebski:
Large Scale Structure of Neural Network Loss Landscapes. NeurIPS 2019: 6706-6714 - [i16]Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, Sylvain Gelly:
Parameter-Efficient Transfer Learning for NLP. CoRR abs/1902.00751 (2019) - [i15]Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor, Lukasz Maziarka, Stanislaw Jastrzebski:
Non-linear ICA based on Cramer-Wold metric. CoRR abs/1903.00201 (2019) - [i14]Nan Wu, Jason Phang, Jungkyu Park, Yiqiu Shen, Zhe Huang, Masha Zorin, Stanislaw Jastrzebski, Thibault Févry, Joe Katsnelson, Eric Kim, Stacey Wolfson, Ujas Parikh, Sushma Gaddam, Leng Leng Young Lin, Kara Ho, Joshua D. Weinstein, Beatriu Reig, Yiming Gao, Hildegard Toth, Kristine Pysarenko, Alana Lewin, Jiyon Lee, Krystal Airola, Eralda Mema, Stephanie Chung, Esther Hwang, Naziya Samreen, Sungheon Gene Kim, Laura Heacock, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras:
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening. CoRR abs/1903.08297 (2019) - [i13]Michal Zajac, Konrad Zolna, Stanislaw Jastrzebski:
Split Batch Normalization: Improving Semi-Supervised Learning under Domain Shift. CoRR abs/1904.03515 (2019) - [i12]Stanislav Fort, Stanislaw Jastrzebski:
Large Scale Structure of Neural Network Loss Landscapes. CoRR abs/1906.04724 (2019) - 2018
- [c6]Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. ICANN (3) 2018: 392-402 - [c5]Stanislaw Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio:
Residual Connections Encourage Iterative Inference. ICLR (Poster) 2018 - [c4]Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
Finding Flatter Minima with SGD. ICLR (Workshop) 2018 - [i11]Stanislaw Jastrzebski, Dzmitry Bahdanau, Seyedarian Hosseini, Michael Noukhovitch, Yoshua Bengio, Jackie Chi Kit Cheung:
Commonsense mining as knowledge base completion? A study on the impact of novelty. CoRR abs/1804.09259 (2018) - [i10]Jacek Tabor, Szymon Knop, Przemyslaw Spurek, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski:
Cramer-Wold AutoEncoder. CoRR abs/1805.09235 (2018) - [i9]Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
DNN's Sharpest Directions Along the SGD Trajectory. CoRR abs/1807.05031 (2018) - [i8]Wojciech Tarnowski, Piotr Warchol, Stanislaw Jastrzebski, Jacek Tabor, Maciej A. Nowak:
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function. CoRR abs/1809.08848 (2018) - [i7]Quentin de Laroussilhe, Stanislaw Jastrzebski, Neil Houlsby, Andrea Gesmundo:
Neural Architecture Search Over a Graph Search Space. CoRR abs/1812.10666 (2018) - 2017
- [c3]David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville:
Deep Nets Don't Learn via Memorization. ICLR (Workshop) 2017 - [c2]Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien:
A Closer Look at Memorization in Deep Networks. ICML 2017: 233-242 - [i6]Stanislaw Jastrzebski, Damian Lesniak, Wojciech Marian Czarnecki:
How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks. CoRR abs/1702.02170 (2017) - [i5]Dzmitry Bahdanau, Tom Bosc, Stanislaw Jastrzebski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio:
Learning to Compute Word Embeddings On the Fly. CoRR abs/1706.00286 (2017) - [i4]Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien:
A Closer Look at Memorization in Deep Networks. CoRR abs/1706.05394 (2017) - [i3]Stanislaw Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio:
Residual Connections Encourage Iterative Inference. CoRR abs/1710.04773 (2017) - [i2]Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
Three Factors Influencing Minima in SGD. CoRR abs/1711.04623 (2017) - 2016
- [j1]Robert T. McGibbon, Carlos X. Hernández, Matthew P. Harrigan, Steven Kearnes, Mohammad M. Sultan, Stanislaw Jastrzebski, Brooke E. Husic, Vijay S. Pande:
Osprey: Hyperparameter Optimization for Machine Learning. J. Open Source Softw. 1(5): 34 (2016) - [i1]Stanislaw Jastrzebski, Damian Lesniak, Wojciech Marian Czarnecki:
Learning to SMILE(S). CoRR abs/1602.06289 (2016) - 2013
- [c1]Igor T. Podolak, Stanislaw K. Jastrzebski:
Density Invariant Detection of Osteoporosis Using Growing Neural Gas. CORES 2013: 629-638
Coauthor Index
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