Blake Bordelon

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Cengiz PehlevanHarvard UniversityDirección de correo verificada de seas.harvard.edu
Abdulkadir CanatarFlatiron InstituteDirección de correo verificada de g.harvard.edu
Alexander AtanasovPhD, Harvard UniversityDirección de correo verificada de g.harvard.edu
Haozhe ShanARNI Postdoctoral Fellow, Columbia UniversityDirección de correo verificada de g.harvard.edu
Hossein MahzoonWashington University in St. Louis, Michigan State University, Truman state UniversityDirección de correo verificada de physics.wustl.edu
MC AtkinsonPostdoc at Lawrence Livermore National LaboratoryDirección de correo verificada de triumf.ca
Dickhoff W HProfessor of Physics, Washington UniversityDirección de correo verificada de wuphys.wustl.edu
Cole D. Pruitt, PhDLawrence Livermore National LaboratoryDirección de correo verificada de llnl.gov
Rylan SchaefferStanford UniversityDirección de correo verificada de stanford.edu
Mikail KhonaResearch Scientist, NVIDIADirección de correo verificada de nvidia.com
Ila FieteProfessor of Brain and Cognitive Sciences, MITDirección de correo verificada de mit.edu
Shubhendu TrivediMassachusetts Institute of TechnologyDirección de correo verificada de csail.mit.edu
Benjamin MoseleyCarnegie Mellon UniversityDirección de correo verificada de andrew.cmu.edu
Ralf WesselProfessor of Physics, Washington University in Saint LouisDirección de correo verificada de physics.wustl.edu
Bryce Allen BagleyMD candidate, Stanford UniversityDirección de correo verificada de stanford.edu

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Blake Bordelon

Applied Mathematics at Harvard

Dirección de correo verificada de g.harvard.edu

Machine Learning Theoretical Neuroscience


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Spectrum dependent learning curves in kernel regression and wide neural networks B Bordelon, A Canatar, C Pehlevan International Conference on Machine Learning, 1024-1034, 2020	204	2020
Spectral bias and task-model alignment explain generalization in kernel regression and infinitely wide neural networks A Canatar, B Bordelon, C Pehlevan Nature communications 12 (1), 2914, 2021	189	2021
Neural networks as kernel learners: The silent alignment effect A Atanasov, B Bordelon, C Pehlevan arXiv preprint arXiv:2111.00034, 2021	78	2021
Self-consistent dynamical field theory of kernel evolution in wide neural networks B Bordelon, C Pehlevan Advances in Neural Information Processing Systems 35, 32240-32256, 2022	69	2022
Dispersive optical model analysis of generating a neutron-skin prediction beyond the mean field MC Atkinson, MH Mahzoon, MA Keim, BA Bordelon, CD Pruitt, RJ Charity, ... Physical Review C 101 (4), 044303, 2020	40	2020
Dynamics of finite width kernel and prediction fluctuations in mean field neural networks B Bordelon, C Pehlevan Advances in Neural Information Processing Systems 36, 2024	27	2024
Grokking as the transition from lazy to rich training dynamics T Kumar, B Bordelon, SJ Gershman, C Pehlevan arXiv preprint arXiv:2310.06110, 2023	26	2023
The onset of variance-limited behavior for networks in the lazy and rich regimes A Atanasov, B Bordelon, S Sainathan, C Pehlevan arXiv preprint arXiv:2212.12147, 2022	24	2022
The influence of learning rule on representation dynamics in wide neural networks B Bordelon, C Pehlevan The Eleventh International Conference on Learning Representations, 2022	24	2022
Learning Curves for SGD on Structured Features B Bordelon, C Pehlevan International Conference on Learning Representations, 2022	24	2022
A dynamical model of neural scaling laws B Bordelon, A Atanasov, C Pehlevan arXiv preprint arXiv:2402.01092, 2024	22	2024
Feature-learning networks are consistent across widths at realistic scales N Vyas, A Atanasov, B Bordelon, D Morwani, S Sainathan, C Pehlevan Advances in Neural Information Processing Systems 36, 2024	21	2024
Out-of-distribution generalization in kernel regression A Canatar, B Bordelon, C Pehlevan Advances in Neural Information Processing Systems 34, 12600-12612, 2021	19	2021
Population codes enable learning from few examples by shaping inductive bias B Bordelon, C Pehlevan Elife 11, e78606, 2022	18	2022
A theory of neural tangent kernel alignment and its influence on training H Shan, B Bordelon arXiv preprint arXiv:2105.14301, 2021	18*	2021
Depthwise hyperparameter transfer in residual networks: Dynamics and scaling limit B Bordelon, L Noci, MB Li, B Hanin, C Pehlevan arXiv preprint arXiv:2309.16620, 2023	16	2023
Infinite Limits of Multi-head Transformer Dynamics B Bordelon, HT Chaudhry, C Pehlevan arXiv preprint arXiv:2405.15712, 2024	5	2024
Loss dynamics of temporal difference reinforcement learning B Bordelon, P Masset, H Kuo, C Pehlevan Advances in Neural Information Processing Systems 36, 2024	5	2024
Self-consistent dynamical field theory of kernel evolution in wide neural networks B Bordelon, C Pehlevan Journal of Statistical Mechanics: Theory and Experiment 2023 (11), 114009, 2023	5	2023
Efficient online inference for nonparametric mixture models R Schaeffer, B Bordelon, M Khona, W Pan, IR Fiete Uncertainty in Artificial Intelligence, 2072-2081, 2021	4	2021

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