Παρακολούθηση
David Rolnick
David Rolnick
McGill University, Mila Quebec AI Institute
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα cs.mcgill.ca - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
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
984*2022
Experience replay for continual learning
D Rolnick, A Ahuja, J Schwarz, TP Lillicrap, G Wayne
Advances in Neural Information Processing Systems, 2019
8632019
Why does deep and cheap learning work so well?
HW Lin, M Tegmark, D Rolnick
Journal of Statistical Physics 168, 1223-1247, 2017
7522017
Deep learning is robust to massive label noise
D Rolnick, A Veit, S Belongie, N Shavit
arXiv preprint arXiv:1705.10694, 2017
6372017
How to start training: The effect of initialization and architecture
B Hanin, D Rolnick
Advances in Neural Information Processing Systems, 2018
2632018
Complexity of linear regions in deep networks
B Hanin, D Rolnick
International Conference on Machine Learning, 2596-2604, 2019
2212019
The power of deeper networks for expressing natural functions
D Rolnick, M Tegmark
International Conference on Learning Representations, 2018
2212018
Deep ReLU networks have surprisingly few activation patterns
B Hanin, D Rolnick
Advances in Neural Information Processing Systems, 361-370, 2019
2152019
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
1642022
DC3: A learning method for optimization with hard constraints
PL Donti, D Rolnick, JZ Kolter
International Conference on Learning Representations, 2021
1412021
Measuring and regularizing networks in function space
AS Benjamin, D Rolnick, K Kording
International Conference on Learning Representations, 2019
1402019
Reverse-engineering deep ReLU networks
D Rolnick, K Kording
International Conference on Machine Learning, 8178-8187, 2020
942020
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
432016
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, 479-509, 2022
392022
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
362019
Morphological error detection in 3D segmentations
D Rolnick, Y Meirovitch, T Parag, H Pfister, V Jain, JW Lichtman, ...
arXiv preprint arXiv:1705.10882, 2017
252017
Bugs in the data: How ImageNet misrepresents biodiversity
AS Luccioni, D Rolnick
AAAI Conference on Artificial Intelligence, 2022
242022
Techniques for symbol grounding with satnet
S Topan, D Rolnick, X Si
Advances in Neural Information Processing Systems 34, 20733-20744, 2021
222021
Artificial Intelligence and Climate Change: Opportunities, considerations, and policy levers to align AI with climate change goals
LH Kaack, PL Donti, E Strubell, D Rolnick
212020
Graph-coloring ideals: Nullstellensatz certificates, Gröbner bases for chordal graphs, and hardness of Gröbner bases
JA De Loera, S Margulies, M Pernpeintner, E Riedl, D Rolnick, G Spencer, ...
Proceedings of the 2015 ACM on International Symposium on Symbolic and …, 2015
21*2015
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