Stanisław Jastrzębski
Stanisław Jastrzębski
Postdoctoral Fellow, New York University
Zweryfikowany adres z nyu.edu - Strona główna
TytułCytowane przezRok
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
263*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
1092017
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
372017
Learning to SMILE(S)
S Jastrzebski, D Lesniak, WM Czarnecki
International Conference on Learning Representation 2016 (Workshop track), 2016
36*2016
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
332017
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
312017
Osprey: Hyperparameter Optimization for Machine Learning.
RT McGibbon, CX Hernández, MP Harrigan, SM Kearnes, MM Sultan, ...
J. Open Source Software 1 (5), 34, 2016
242016
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, ...
202019
Parameter-Efficient Transfer Learning for NLP
N Houlsby, A Giurgiu*, S Jastrzebski*, B Morrone, Q Laroussilhe, ...
International Conference on Machine Learning (ICML) 2019, 2019
192019
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
16*2019
Cramer-Wold AutoEncoder
J Tabor, S Knop, P Spurek, I Podolak, M Mazur, S Jastrzebski
arXiv preprint arXiv:1805.09235, 2018
132018
Stiffness: A new perspective on generalization in neural networks
S Fort, PK Nowak, S Jastrzebski, S Narayanan
arXiv preprint arXiv:1901.09491, 2019
92019
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
82018
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
62018
Evolutionary-Neural Hybrid Agents for Architecture Search
K Maziarz, A Khorlin, Q de Laroussilhe, S Jastrzebski, T Mingxing, ...
arXiv preprint arXiv:1811.09828, 2018
42018
Density Invariant Detection of Osteoporosis Using Growing Neural Gas
IT Podolak, SK Jastrzebski
Proceedings of the 8th International Conference on Computer Recognition …, 2013
42013
Large Scale Structure of Neural Network Loss Landscapes
S Fort, S Jastrzebski
NeurIPS 2019, 2019
32019
Quo vadis G Protein-Coupled Receptor ligands? A tool for analysis of the emergence of new groups of compounds over time
AJB Damian Lesniak, Stanislaw Jastrzebski, Sabina Podlewska, Wojciech M ...
Bioorganic & Medicinal Chemistry Letters, 2016
3*2016
Three-dimensional descriptors for aminergic GPCRs: dependence on docking conformation and crystal structure
S Jastrzebski, I Sieradzki, D Leśniak, J Tabor, AJ Bojarski, S Podlewska
Molecular Diversity, 1-11, 2018
22018
Analysis of compounds activity concept learned by SVM using robust Jaccard based low-dimensional embedding
S Jastrzebski, WM Czarnecki
Schedae Informaticae 24, 9-19, 2016
22016
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Prace 1–20