Stanisław Jastrzębski - Google Scholar

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	Toutes	Depuis 2015
Citations	1043	1043
indice h	13	13
indice i10	15	15

420

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105

315

201620172018201920207 47 196 364 418

Coauteurs

Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARAdresse e-mail validée de umontreal.ca
Nicolas BallasFacebook AI ResearchAdresse e-mail validée de fb.com
Asja FischerProfessor for Machine Learning, Ruhr University BochumAdresse e-mail validée de ini.rub.de
Devansh ArpitSenior Research Scientist, SalesforceAdresse e-mail validée de salesforce.com
Amos StorkeyProfessor of Machine Learning and AI, School of Informatics, University of Edinburgh, UKAdresse e-mail validée de ed.ac.uk
Zachary KentonUniversity of OxfordAdresse e-mail validée de cs.ox.ac.uk
Emmanuel BengioMcGill UniversityAdresse e-mail validée de mail.mcgill.ca
David Scott KruegerPhD Student, University of MontrealAdresse e-mail validée de umontreal.ca
Tegan MaharajPhD student, MILA (Polytechnique Montreal)Adresse e-mail validée de polymtl.ca
Maxinder S. KanwalPhD Student, Stanford UniversityAdresse e-mail validée de stanford.edu
Jacek TaborProfesor informatyki, Uniwersytet JagiellońskiAdresse e-mail validée de ii.uj.edu.pl
Aaron CourvilleUniversité de MontréalAdresse e-mail validée de umontreal.ca
Simon Lacoste-JulienAssociate Professor - Canada CIFAR AI Chair, University of Montreal / MilaAdresse e-mail validée de iro.umontreal.ca
Wojciech Marian CzarneckiResearch Scientist at DeepMindAdresse e-mail validée de google.com
Andrea GesmundoGoogleAdresse e-mail validée de google.com
Neil HoulsbyGoogleAdresse e-mail validée de google.com
Quentin de LaroussilheGoogleAdresse e-mail validée de google.com
Stanislav FortGraduate student, Stanford University / Google AIAdresse e-mail validée de stanford.edu
Sylvain GellyGoogle Brain ZurichAdresse e-mail validée de m4x.org
Sabina PodlewskaInstitute of Pharmacology Polish Academy of SciencesAdresse e-mail validée de if-pan.krakow.pl

Stanisław Jastrzębski

Postdoctoral Fellow, New York University

Adresse e-mail validée de nyu.edu - Page d'accueil

Deep Learning Drug Discovery Optimization


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
A Closer Look at Memorization in Deep Networks D Arpit, S Jastrzebski, N Ballas, D Krueger, E Bengio, MS Kanwal, ... International Conference on Machine Learning 2017, 2017	404*	2017
Three factors influencing minima in SGD S Jastrzebski, Z Kenton, D Arpit, N Ballas, A Fischer, Y Bengio, ... International Conference on Artificial Neural Networks 2018; International …, 2017	160	2017
Parameter-Efficient Transfer Learning for NLP N Houlsby, A Giurgiu, S Jastrzebski, B Morrone, Q Laroussilhe, ... International Conference on Machine Learning (ICML) 2019, 2019	66	2019
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening N Wu, J Phang, J Park, Y Shen, Z Huang, M Zorin, S Jastrzebski, T Févry, ...	53	2019
Residual connections encourage iterative inference S Jastrzebski, D Arpit, N Ballas, V Verma, T Che, Y Bengio International Conference on Learning Algorithms (ICLR) 2018, 2017	51	2017
How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks S Jastrzebski, D Leśniak, WM Czarnecki arXiv preprint arXiv:1702.02170, 2017	46	2017
Learning to SMILE(S) S Jastrzebski, D Lesniak, WM Czarnecki International Conference on Learning Representation 2016 (Workshop track), 2016	46*	2016
Learning to Compute Word Embeddings on the Fly D Bahdanau, T Bosc, S Jastrzebski, E Grefenstette, P Vincent, Y Bengio Montreal AI Symposium 2017, 2017	44	2017
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length S Jastrzębski, Z Kenton, N Ballas, A Fischer, Y Bengio, A Storkey International Conference on Learning Algorithms (ICLR) 2019, 2019	29*	2019
Osprey: Hyperparameter optimization for machine learning R McGibbon, C Hernández, M Harrigan, S Kearnes, M Sultan, ... Journal of Open Source Software 1 (5), 34, 2016	27	2016
Stiffness: A new perspective on generalization in neural networks S Fort, PK Nowak, S Jastrzebski, S Narayanan arXiv preprint arXiv:1901.09491, 2019	19	2019
Cramer-Wold Auto-Encoder S Knop, P Spurek, J Tabor, I Podolak, M Mazur, S Jastrzębski Journal of Machine Learning Research 21 (164), 1-28, 2020	17	2020
Evolutionary-Neural Hybrid Agents for Architecture Search K Maziarz, A Khorlin, Q de Laroussilhe, S Jastrzebski, T Mingxing, ... arXiv preprint arXiv:1811.09828, 2018	14*	2018
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function W Tarnowski, P Warchoł, S Jastrzebski, J Tabor, M Nowak AISTATS 2019, 2018	12	2018
Large Scale Structure of Neural Network Loss Landscapes S Fort, S Jastrzebski NeurIPS 2019, 2019	11	2019
The Break-Even Point on Optimization Trajectories of Deep Neural Networks S Jastrzebski, M Szymczak, S Fort, D Arpit, J Tabor, K Cho, K Geras International Conference on Learning Algorithms (ICLR) 2020, 2020	9	2020
Commonsense mining as knowledge base completion? A study on the impact of novelty S Jastrzebski, D Bahdanau, S Hosseini, M Noukhovitch, Y Bengio, ... New Forms of Generalization in Deep Learning and Natural Language Processing …, 2018	8	2018
Molecule Attention Transformer Ł Maziarka, T Danel, S Mucha, K Rataj, J Tabor, S Jastrzębski arXiv preprint arXiv:2002.08264, 2020	5	2020
Density Invariant Detection of Osteoporosis Using Growing Neural Gas IT Podolak, SK Jastrzebski Proceedings of the 8th International Conference on Computer Recognition …, 2013	5	2013
Development of new methods needs proper evaluation – benchmarking sets for machine learning experiments for class A GPCRs D Leśniak, S Podlewska, S Jastrzebski, I Sieradzki, A Bojarski, J Tabor J. Chem. Inf. Model, 2019	4	2019

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