Stanislaw Jastrzebski

According to our database, Stanislaw Jastrzebski authored at least 47 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Relative molecule self-attention transformer.

Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski

J. Cheminformatics, December, 2024

An Efficient Deep Neural Network to Classify Large 3D Images With Small Objects.

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

IEEE Trans. Medical Imaging, January, 2024

Generative Active Learning for the Search of Small-molecule Protein Binders.

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

CoRR, 2024

2023

Generative Models Should at Least Be Able to Design Molecules That Dock Well: A New Benchmark.

Tobiasz Cieplinski, Tomasz Danel, Sabina Podlewska, Stanislaw Jastrzebski

J. Chem. Inf. Model., June, 2023

Molecule-Edit Templates for Efficient and Accurate Retrosynthesis Prediction.

Mikolaj Sacha, Michal Sadowski, Piotr Kozakowski, Ruard van Workum, Stanislaw Jastrzebski

CoRR, 2023

2022

RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software.

Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler

J. Chem. Inf. Model., 2022

3D-GMIC: an efficient deep neural network to find small objects in large 3D images.

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

CoRR, 2022

Characterizing and Overcoming the Greedy Nature of Learning in Multi-modal Deep Neural Networks.

Nan Wu, Stanislaw Jastrzebski, Kyunghyun Cho, Krzysztof J. Geras

Proceedings of the International Conference on Machine Learning, 2022

HuggingMolecules: An Open-Source Library for Transformer-Based Molecular Property Prediction (Student Abstract).

Piotr Gainski, Lukasz Maziarka, Tomasz Danel, Stanislaw Jastrzebski

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

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

npj Digit. Medicine, 2021

Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits.

Mikolaj Sacha, Mikolaj Blaz, Piotr Byrski, Pawel Dabrowski-Tumanski, Mikolaj Chrominski, Rafal Loska, Pawel Wlodarczyk-Pruszynski, Stanislaw Jastrzebski

J. Chem. Inf. Model., 2021

Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization.

Stanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J. Geras

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.

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

IEEE Trans. Medical Imaging, 2020

Cramer-Wold Auto-Encoder.

Szymon Knop, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski

J. Mach. Learn. Res., 2020

Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening.

Stanislaw Jastrzebski, Maciej Szymczak, Agnieszka Pocha, Stefan Mordalski, Jacek Tabor, Andrzej J. Bojarski, Sabina Podlewska

J. Chem. Inf. Model., 2020

Differences between human and machine perception in medical diagnosis.

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

CoRR, 2020

RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design.

Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler

CoRR, 2020

Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks.

Luke Nicholas Darlow, Stanislaw Jastrzebski, Amos J. Storkey

CoRR, 2020

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

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

CoRR, 2020

We should at least be able to Design Molecules that Dock Well.

Tobiasz Cieplinski, Tomasz Danel, Sabina Podlewska, Stanislaw Jastrzebski

CoRR, 2020

Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits.

Mikolaj Sacha, Mikolaj Blaz, Piotr Byrski, Pawel Wlodarczyk-Pruszynski, Stanislaw Jastrzebski

CoRR, 2020

Understanding the robustness of deep neural network classifiers for breast cancer screening.

Witold Oleszkiewicz, Taro Makino, Stanislaw Jastrzebski, Tomasz Trzcinski, Linda Moy, Kyunghyun Cho, Laura Heacock, Krzysztof J. Geras

CoRR, 2020

Molecule Attention Transformer.

Lukasz Maziarka, Tomasz Danel, Slawomir Mucha, Krzysztof Rataj, Jacek Tabor, Stanislaw Jastrzebski

CoRR, 2020

Improving the Ability of Deep Neural Networks to Use Information from Multiple Views in Breast Cancer Screening.

Nan Wu, Stanislaw Jastrzebski, Jungkyu Park, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Non-linear ICA Based on Cramer-Wold Metric.

Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor, Lukasz Maziarka, Stanislaw Jastrzebski

Proceedings of the Neural Information Processing - 27th International Conference, 2020

The Break-Even Point on Optimization Trajectories of Deep Neural Networks.

Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Development of New Methods Needs Proper Evaluation - Benchmarking Sets for Machine Learning Experiments for Class A GPCRs.

Damian Lesniak, Sabina Podlewska, Stanislaw Jastrzebski, Igor Sieradzki, Andrzej J. Bojarski, Jacek Tabor

J. Chem. Inf. Model., 2019

Split Batch Normalization: Improving Semi-Supervised Learning under Domain Shift.

Michal Zajac, Konrad Zolna, Stanislaw Jastrzebski

CoRR, 2019

Large Scale Structure of Neural Network Loss Landscapes.

Stanislav Fort, Stanislaw Jastrzebski

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Parameter-Efficient Transfer Learning for NLP.

Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, Sylvain Gelly

Proceedings of the 36th International Conference on Machine Learning, 2019

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length.

Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey

Proceedings of the 7th International Conference on Learning Representations, 2019

Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function.

Wojciech Tarnowski, Piotr Warchol, Stanislaw Jastrzebski, Jacek Tabor, Maciej A. Nowak

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Neural Architecture Search Over a Graph Search Space.

Quentin de Laroussilhe, Stanislaw Jastrzebski, Neil Houlsby, Andrea Gesmundo

CoRR, 2018

DNN's Sharpest Directions Along the SGD Trajectory.

Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey

CoRR, 2018

Cramer-Wold AutoEncoder.

Jacek Tabor, Szymon Knop, Przemyslaw Spurek, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski

CoRR, 2018

Commonsense mining as knowledge base completion? A study on the impact of novelty.

Stanislaw Jastrzebski, Dzmitry Bahdanau, Seyedarian Hosseini, Michael Noukhovitch, Yoshua Bengio, Jackie Chi Kit Cheung

CoRR, 2018

Finding Flatter Minima with SGD.

Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey

Proceedings of the 6th International Conference on Learning Representations, 2018

Residual Connections Encourage Iterative Inference.

Stanislaw Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio

Proceedings of the 6th International Conference on Learning Representations, 2018

Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio.

Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

2017

Three Factors Influencing Minima in SGD.

Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey

CoRR, 2017

How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks.

Stanislaw Jastrzebski, Damian Lesniak, Wojciech Marian Czarnecki

CoRR, 2017

Learning to Compute Word Embeddings On the Fly.

Dzmitry Bahdanau, Tom Bosc, Stanislaw Jastrzebski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio

CoRR, 2017

A Closer Look at Memorization in Deep Networks.

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

Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Nets Don't Learn via Memorization.

David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Osprey: Hyperparameter Optimization for Machine Learning.

Robert T. McGibbon, Carlos X. Hernández, Matthew P. Harrigan, Steven Kearnes, Mohammad M. Sultan, Stanislaw Jastrzebski, Brooke E. Husic, Vijay S. Pande

J. Open Source Softw., 2016

Learning to SMILE(S).

Stanislaw Jastrzebski, Damian Lesniak, Wojciech Marian Czarnecki

CoRR, 2016

2013

Density Invariant Detection of Osteoporosis Using Growing Neural Gas.

Igor T. Podolak, Stanislaw K. Jastrzebski

Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013, 2013