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; Prof., U. Toronto (Statistics, CS)Verified email at utoronto.ca
Jose Javier Gonzalez OrtizMassachusetts Institute of TechnologyVerified email at mit.edu
Ari S. MorcosDatologyAIVerified email at datologyai.com
Mansheej PaulResearch Scientist, DatabricksVerified email at databricks.com
Alex RendaPhD Student, MITVerified email at csail.mit.edu
Zhangyang (Atlas) WangXTX Markets & University of Texas at AustinVerified email at utexas.edu
Brett W. LarsenDatabricks Mosaic ResearchVerified email at stanford.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 nyu.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

Verified email at databricks.com - Homepage

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	4192	2019
What is the State of Neural Network Pruning? D Blalock, JJG Ortiz, J Frankle, J Guttag Conference on Machine Learning and Systems, 2020	1306	2020
Linear Mode Connectivity and the Lottery Ticket Hypothesis J Frankle, GK Dziugaite, DM Roy, M Carbin International Conference on Machine Learning, 2020	566	2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning A Renda, J Frankle, M Carbin International Conference on Learning Representations, 2020	436	2020
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	393	2020
The Perpetual Line-Up: Unregulated Police Face Recognition in America C Garvie, A Bedoya, J Frankle Georgetown Law, Center on Privacy & Technology, 2016	389	2016
Stabilizing the Lottery Ticket Hypothesis / The Lottery Ticket Hypothesis at Scale J Frankle, GK Dziugaite, DM Roy, M Carbin arXiv, 2019	372*	2019
Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs MMLNLP Team https://www.databricks.com/blog/mpt-7b, 2023	257*	2023
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	247	2021
The Early Phase of Neural Network Training J Frankle, DJ Schwab, AS Morcos International Conference on Learning Representations, 2020	180	2020
Example-Directed Synthesis: A Type-Theoretic Interpretation J Frankle, PM Osera, D Walker, S Zdancewic POPL 51 (1), 802-815, 2016	154	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	140	2021
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	138	2021
Facial-Recognition Software Might Have a Racial Bias Problem C Garvie, J Frankle The Atlantic 7, 2016	133	2016
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	88	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	84*	2021
Desirable Inefficiency P Ohm, J Frankle Fla. L. Rev. 70, 777, 2018	69	2018
Lora learns less and forgets less D Biderman, J Portes, JJG Ortiz, M Paul, P Greengard, C Jennings, ... arXiv preprint arXiv:2405.09673, 2024	61	2024
The shift from models to compound ai systems M Zaharia, O Khattab, L Chen, JQ Davis, H Miller, C Potts, J Zou, ... Berkeley Artificial Intelligence Research Lab. Available online at: https …, 2024	55	2024
MPT-30B: Raising the Bar for Open-Source Foundation Models MMLNLP Team https://www.databricks.com/blog/mpt-30b, 2023	40*	2023

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