Jonathan Frankle

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Michael CarbinMassachusetts Institute of TechnologyVerified email at csail.mit.edu
Gintare Karolina DziugaiteGoogle DeepMindVerified email at google.com
Daniel M. RoyResearch Director, Vector Institute; Assoc. Prof., U. Toronto (Statistics, CS)Verified email at utoronto.ca
Ari S. MorcosDatologyAIVerified email at datologyai.com
Jose Javier Gonzalez OrtizMassachusetts Institute of TechnologyVerified email at mit.edu
Alex RendaPhD Student, MITVerified email at csail.mit.edu
Peter-Michael OseraGrinnell CollegeVerified email at cs.grinnell.edu
Daniel J. Weitzner3Com Founders Senior Research Scientist, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Sunoo ParkMITVerified email at csail.mit.edu
Steve ZdancewicProfessor of Computer and Information Science, University of PennsylvaniaVerified email at cis.upenn.edu
David WalkerPrinceton UniversityVerified email at cs.princeton.edu
Jonathan S. RosenfeldPhD, Computer Science, MITVerified email at csail.mit.edu
Saman AmarasingheMITVerified email at mit.edu
Riyadh BaghdadiAssistant Professor (NYUAD); Global Network Assistant Professor (NYU); Research Affiliate (MIT)Verified email at mit.edu
BENHAMIDA Fatima ZohraAssistant professor at Ecole Nationale Superieure d'InformatiqueVerified email at esi.dz
Abdelkader Nadir DebbaghEtudiant, Ecole Nationale Supérieure d'InformatiqueVerified email at esi.dz
David BauAssistant Professor at Northeastern UniversityVerified email at northeastern.edu

Jonathan Frankle

Databricks - Mosaic Research

Verified email at databricks.com - Homepage

Empirical Deep Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks J Frankle, M Carbin International Conference on Learning Representations, 2019	3383	2019
What is the State of Neural Network Pruning? D Blalock, JJG Ortiz, J Frankle, J Guttag Conference on Machine Learning and Systems, 2020	1076	2020
Linear Mode Connectivity and the Lottery Ticket Hypothesis J Frankle, GK Dziugaite, DM Roy, M Carbin International Conference on Machine Learning, 2020	428	2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning A Renda, J Frankle, M Carbin International Conference on Learning Representations, 2020	384	2020
Stabilizing the Lottery Ticket Hypothesis / The Lottery Ticket Hypothesis at Scale J Frankle, GK Dziugaite, DM Roy, M Carbin arXiv, 2019	339*	2019
The Perpetual Line-Up: Unregulated Police Face Recognition in America C Garvie, A Bedoya, J Frankle Georgetown Law, Center on Privacy & Technology, 2016	339	2016
The Lottery Ticket Hypothesis for Pre-Trained BERT Networks T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin Neural Information Processing Systems, 2020	332	2020
Pruning Neural Networks at Initialization: Why are We Missing the Mark? J Frankle, GK Dziugaite, DM Roy, M Carbin International Conference on Learning Representations, 2021	196	2021
The lottery ticket hypothesis: Training pruned neural networks J Frankle, M Carbin arXiv preprint arXiv:1803.03635 2, 2018	175	2018
The Early Phase of Neural Network Training J Frankle, DJ Schwab, AS Morcos International Conference on Learning Representations, 2020	156	2020
Example-Directed Synthesis: A Type-Theoretic Interpretation J Frankle, PM Osera, D Walker, S Zdancewic POPL 51 (1), 802-815, 2016	142	2016
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs J Frankle, DJ Schwab, AS Morcos International Conference on Learning Representations, 2021	122	2021
Facial-Recognition Software Might Have a Racial Bias Problem C Garvie, J Frankle The Atlantic 7, 2016	121	2016
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models T Chen, J Frankle, S Chang, S Liu, Y Zhang, M Carbin, Z Wang Conference on Computer Vision and Pattern Recognition, 2021	119	2021
Practical Accountability of Secret Processes J Frankle, S Park, D Shaar, S Goldwasser, D Weitzner 27th USENIX Security Symposium (USENIX Security 18), 657-674, 2018	83	2018
Are all negatives created equal in contrastive instance discrimination? TT Cai, J Frankle, DJ Schwab, AS Morcos Science Meets Engineering of Deep Learning Workshop (ICLR), 2021	67*	2021
Desirable Inefficiency P Ohm, J Frankle Fla. L. Rev. 70, 777, 2018	61	2018
On the Predictability of Pruning Across Scales JS Rosenfeld, J Frankle, M Carbin, N Shavit International Conference on Machine Learning, 2021	31	2021
Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? M Paul, F Chen, BW Larsen, J Frankle, S Ganguli, GK Dziugaite arXiv preprint arXiv:2210.03044, 2022	27	2022
What can linear interpolation of neural network loss landscapes tell us? TJ Vlaar, J Frankle International Conference on Machine Learning, 22325-22341, 2022	20	2022

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