Stanisław Jastrzębski
Stanisław Jastrzębski
Postdoctoral Fellow, New York University
Verified email at student.uj.edu.pl - Homepage
TitleCited byYear
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
185*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
732017
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
292017
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
252017
Learning to SMILE(S)
S Jastrzebski, D Lesniak, WM Czarnecki
International Conference on Learning Representation 2016 (Workshop track), 2016
25*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
242017
Osprey: Hyperparameter Optimization for Machine Learning.
RT McGibbon, CX Hernández, MP Harrigan, SM Kearnes, MM Sultan, ...
J. Open Source Software 1 (5), 34, 2016
192016
Cramer-Wold AutoEncoder
J Tabor, S Knop, P Spurek, I Podolak, M Mazur, S Jastrzebski
arXiv preprint arXiv:1805.09235, 2018
102018
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length
S Jastrzebski, Z Kenton, N Ballas, A Fischer, Y Bengio, A Storkey
International Conference on Learning Algorithms (ICLR) 2019, 2018
8*2018
Parameter-Efficient Transfer Learning for NLP
N Houlsby, A Giurgiu*, S Jastrzebski*, B Morrone, Q Laroussilhe, ...
International Conference on Machine Learning (ICML) 2019, 2019
62019
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
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
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, ...
22019
Evolutionary-Neural Hybrid Agents for Architecture Search
K Maziarz, A Khorlin, Q de Laroussilhe, S Jastrzebski, T Mingxing, ...
arXiv preprint arXiv:1811.09828, 2018
22018
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
22018
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
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
2*2016
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
On Certain Limitations of Recursive Representation Model
S Jastrzebski, I Sieradzki
Schedae Informaticae 25, 37-47, 2017
12017
Large Scale Structure of Neural Network Loss Landscapes
S Fort, S Jastrzebski
NeurIPS 2019, 2019
2019
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Articles 1–20