Gintare Karolina Dziugaite
Gintare Karolina Dziugaite
Research Scientist, Element AI
Verified email at elementai.com - Homepage
TitleCited byYear
Training generative neural networks via maximum mean discrepancy optimization
GK Dziugaite, DM Roy, Z Ghahramani
arXiv preprint arXiv:1505.03906, 2015
2222015
Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data
GK Dziugaite, DM Roy
arXiv preprint arXiv:1703.11008, 2017
1362017
A study of the effect of jpg compression on adversarial images
GK Dziugaite, Z Ghahramani, DM Roy
arXiv preprint arXiv:1608.00853, 2016
842016
Neural network matrix factorization
GK Dziugaite, DM Roy
arXiv preprint arXiv:1511.06443, 2015
56*2015
Requiem for the max rule?
WJ Ma, S Shen, G Dziugaite, R van den Berg
Vision research 116, 179-193, 2015
192015
Data-dependent PAC-Bayes priors via differential privacy
GK Dziugaite, DM Roy
Advances in Neural Information Processing Systems, 8430-8441, 2018
162018
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Data-dependent PAC-Bayes priors via differential privacy
GK Dziugaite, DM Roy
12*2018
The Lottery Ticket Hypothesis at Scale
J Frankle, GK Dziugaite, DM Roy, M Carbin
arXiv preprint arXiv:1903.01611, 2019
82019
Revisiting Generalization for Deep Learning: PAC-Bayes, Flat Minima, and Generative Models
GK Dziugaite
University of Cambridge, 2020
2020
Stochastic Neural Network with Kronecker Flow
CW Huang, A Touati, P Vincent, GK Dziugaite, A Lacoste, A Courville
arXiv preprint arXiv:1906.04282, 2019
2019
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
J Negrea, M Haghifam, GK Dziugaite, A Khisti, DM Roy
Advances in Neural Information Processing Systems, 11013-11023, 2019
2019
PAC-BAYESIAN GENERALIZATION BOUNDS FOR DEEP NEURAL NETWORKS VIA VARIATIONAL INFERENCE
GK DZIUGAITE, DM ROY
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Articles 1–12