Utku Evci
Utku Evci
Research Engineer @Google Brain
Verified email at nyu.edu - Homepage
Cited by
Cited by
Empirical analysis of the hessian of over-parametrized neural networks
L Sagun, U Evci, VU Guney, Y Dauphin, L Bottou
arXiv preprint arXiv:1706.04454, 2017
Meta-dataset: A dataset of datasets for learning to learn from few examples
E Triantafillou, T Zhu, V Dumoulin, P Lamblin, U Evci, K Xu, R Goroshin, ...
arXiv preprint arXiv:1903.03096, 2019
Rigging the lottery: Making all tickets winners
U Evci, T Gale, J Menick, PS Castro, E Elsen
International Conference on Machine Learning, 2943-2952, 2020
The difficulty of training sparse neural networks
U Evci, F Pedregosa, A Gomez, E Elsen
arXiv preprint arXiv:1906.10732, 2019
Natural language understanding with the quora question pairs dataset
L Sharma, L Graesser, N Nangia, U Evci
arXiv preprint arXiv:1907.01041, 2019
Empirical analysis of the hessian of over-parametrized neural networks. ICLR 2018 Workshop Contribution
L Sagun, U Evci, VU GŁney, Y Dauphin, L Bottou
arXiv preprint arXiv:1706.04454, 2017
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win
U Evci, YA Ioannou, C Keskin, Y Dauphin
arXiv preprint arXiv:2010.03533, 2020
A Practical Sparse Approximation for Real Time Recurrent Learning
J Menick, E Elsen, U Evci, S Osindero, K Simonyan, A Graves
arXiv preprint arXiv:2006.07232, 2020
Detecting dead weights and units in neural networks
U Evci
arXiv preprint arXiv:1806.06068, 2018
One Step from the Locomotion to the Stepping Pattern
R Boulic, U Evci, E Molla, P Pisupati
Proceedings of the 29th International Conference on Computer Animation and†…, 2016
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark
V Dumoulin, N Houlsby, U Evci, X Zhai, R Goroshin, S Gelly, H Larochelle
arXiv preprint arXiv:2104.02638, 2021
Mean Replacement Pruning
U Evci, N Le Roux, P Castro, L Bottou
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