David Rolnick

Citirano

	Sve	Od 2019.
Citati	6126	5714
H-indeks	23	23
i10-indeks	43	40

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Lynn H. KaackHertie SchoolPotvrđena adresa e-pošte na hertie-school.org
Priya L. DontiAssistant Professor, MIT EECS & LIDS; Co-founder and Chair, Climate Change AIPotvrđena adresa e-pošte na mit.edu
Nikola Milojevic-DupontMCC BerlinPotvrđena adresa e-pošte na mcc-berlin.net
Konrad Paul KordingNathan Mossell University Professor (PIK), bioengineering & neuroscience, UPenn, CIFAR LMBPotvrđena adresa e-pošte na upenn.edu
Kelly KochanskiPhD, University of Colorado - BoulderPotvrđena adresa e-pošte na colorado.edu
S. Karthik MukkavilliIBM ResearchPotvrđena adresa e-pošte na ibm.com
Evan D. SherwinStanford UniversityPotvrđena adresa e-pošte na lbl.gov
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARPotvrđena adresa e-pošte na umontreal.ca
Sasha LuccioniHugging FacePotvrđena adresa e-pošte na huggingface.co
Anna Waldman-BrownMIT Industrial Performance CenterPotvrđena adresa e-pošte na alum.mit.edu
Max TegmarkProfessor of Physics, MITPotvrđena adresa e-pošte na mit.edu
Serge BelongieUniversity of CopenhagenPotvrđena adresa e-pošte na di.ku.dk
Kris SankaranUniversity of Wisconsin - MadisonPotvrđena adresa e-pošte na wisc.edu
Andrew RossPhD student, Harvard UniversityPotvrđena adresa e-pošte na g.harvard.edu
Boris HaninAssistant Professor, Princeton ORFEPotvrđena adresa e-pošte na princeton.edu
Felix CreutzigMercator Research Institute on Global Commons and Climate Change & TUB, BerlinPotvrđena adresa e-pošte na mcc-berlin.net
Natasha JaquesUniversity of Washington, Google ResearchPotvrđena adresa e-pošte na google.com
Alexandre LacosteStaff Research Scientist, ServiceNow ResearchPotvrđena adresa e-pošte na servicenow.com
Tegan MaharajAssistant Professor at MilaPotvrđena adresa e-pošte na polymtl.ca
John C. PlattGooglePotvrđena adresa e-pošte na google.com

Prati

David Rolnick

McGill University, Mila Quebec AI Institute

Potvrđena adresa e-pošte na cs.mcgill.ca - Početna stranica

Machine Learning Climate Change Biodiversity Deep Learning Theory


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
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	1162*	2022
Experience replay for continual learning D Rolnick, A Ahuja, J Schwarz, TP Lillicrap, G Wayne Advances in Neural Information Processing Systems, 2019	1034	2019
Why does deep and cheap learning work so well? HW Lin, M Tegmark, D Rolnick Journal of Statistical Physics 168, 1223-1247, 2017	779	2017
Deep learning is robust to massive label noise D Rolnick, A Veit, S Belongie, N Shavit arXiv preprint arXiv:1705.10694, 2017	678	2017
How to start training: The effect of initialization and architecture B Hanin, D Rolnick Advances in Neural Information Processing Systems, 2018	282	2018
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	250	2022
Complexity of linear regions in deep networks B Hanin, D Rolnick International Conference on Machine Learning, 2596-2604, 2019	241	2019
Deep ReLU networks have surprisingly few activation patterns B Hanin, D Rolnick Advances in Neural Information Processing Systems, 361-370, 2019	235	2019
The power of deeper networks for expressing natural functions D Rolnick, M Tegmark International Conference on Learning Representations, 2018	229	2018
DC3: A learning method for optimization with hard constraints PL Donti, D Rolnick, JZ Kolter International Conference on Learning Representations, 2021	169	2021
Measuring and regularizing networks in function space AS Benjamin, D Rolnick, K Kording International Conference on Learning Representations, 2019	147	2019
Reverse-engineering deep ReLU networks D Rolnick, K Kording International Conference on Machine Learning, 8178-8187, 2020	113	2020
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	58	2022
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	43	2016
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	40	2023
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	40	2019
Bugs in the data: How ImageNet misrepresents biodiversity AS Luccioni, D Rolnick AAAI Conference on Artificial Intelligence, 2022	32	2022
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	31	2023
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	28	2024
Climate change and AI: Recommendations for government action P Clutton-Brock, D Rolnick, PL Donti, L Kaack GPAI, Climate Change AI, Centre for AI & Climate, 2021	27*	2021

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