Követés
David Rolnick
David Rolnick
McGill University, Mila Quebec AI Institute
E-mail megerősítve itt: cs.mcgill.ca - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Tackling climate change with machine learning
D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ...
ACM Computing Surveys (CSUR) 55 (2), 1-96, 2022
1405*2022
Experience replay for continual learning
D Rolnick, A Ahuja, J Schwarz, TP Lillicrap, G Wayne
Advances in Neural Information Processing Systems, 2019
12912019
Why does deep and cheap learning work so well?
HW Lin, M Tegmark, D Rolnick
Journal of Statistical Physics 168, 1223-1247, 2017
8272017
Deep learning is robust to massive label noise
D Rolnick, A Veit, S Belongie, N Shavit
arXiv preprint arXiv:1705.10694, 2017
7372017
Aligning artificial intelligence with climate change mitigation
LH Kaack, PL Donti, E Strubell, G Kamiya, F Creutzig, D Rolnick
Nature Climate Change 12 (6), 518-527, 2022
3672022
How to start training: The effect of initialization and architecture
B Hanin, D Rolnick
Advances in Neural Information Processing Systems, 2018
3102018
Complexity of linear regions in deep networks
B Hanin, D Rolnick
International Conference on Machine Learning, 2596-2604, 2019
2772019
Deep ReLU networks have surprisingly few activation patterns
B Hanin, D Rolnick
Advances in Neural Information Processing Systems, 361-370, 2019
2762019
The power of deeper networks for expressing natural functions
D Rolnick, M Tegmark
International Conference on Learning Representations, 2018
2462018
DC3: A learning method for optimization with hard constraints
PL Donti, D Rolnick, JZ Kolter
International Conference on Learning Representations, 2021
2342021
Measuring and regularizing networks in function space
AS Benjamin, D Rolnick, K Kording
International Conference on Learning Representations, 2019
1722019
Reverse-engineering deep ReLU networks
D Rolnick, K Kording
International Conference on Machine Learning, 8178-8187, 2020
1322020
Stealing part of a production language model
N Carlini, D Paleka, KD Dvijotham, T Steinke, J Hayase, AF Cooper, ...
arXiv preprint arXiv:2403.06634, 2024
832024
Digitalization and the Anthropocene
F Creutzig, D Acemoglu, X Bai, PN Edwards, MJ Hintz, LH Kaack, S Kilkis, ...
Annual review of environment and resources 47 (1), 479-509, 2022
812022
Lightweight, pre-trained transformers for remote sensing timeseries
G Tseng, R Cartuyvels, I Zvonkov, M Purohit, D Rolnick, H Kerner
arXiv preprint arXiv:2304.14065, 2023
682023
Faenet: Frame averaging equivariant gnn for materials modeling
AA Duval, V Schmidt, A Hernández-Garcıa, S Miret, FD Malliaros, ...
International Conference on Machine Learning, 9013-9033, 2023
572023
Cross-classification clustering: An efficient multi-object tracking technique for 3-d instance segmentation in connectomics
Y Meirovitch, L Mi, H Saribekyan, A Matveev, D Rolnick, N Shavit
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
462019
Bugs in the data: How ImageNet misrepresents biodiversity
AS Luccioni, D Rolnick
AAAI Conference on Artificial Intelligence, 2022
452022
A multi-pass approach to large-scale connectomics
Y Meirovitch, A Matveev, H Saribekyan, D Budden, D Rolnick, G Odor, ...
arXiv preprint arXiv:1612.02120, 2016
452016
Pushing the frontiers in climate modelling and analysis with machine learning
V Eyring, WD Collins, P Gentine, EA Barnes, M Barreiro, T Beucler, ...
Nature Climate Change 14 (9), 916-928, 2024
432024
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