Boris Hanin 个人学术档案 - 学术资源搜索

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David RolnickMcGill University, Mila Quebec AI Institute在 cs.mcgill.ca 的电子邮件经过验证
Guergana PetrovaTexas A&M University在 tamu.edu 的电子邮件经过验证
Yaiza CanzaniUniversity of North Carolina at Chapel Hill在 email.unc.edu 的电子邮件经过验证
Ronald DeVoreProfessor of Matematics, Texas A&M University在 math.tamu.edu 的电子邮件经过验证
Mihai NicaUniversity of Guelph在 uoguelph.ca 的电子邮件经过验证
Steve ZelditchWayne and Elizabeth Jones Professor of Mathematics, Northwestern University在 math.northwestern.edu 的电子邮件经过验证
Sho YaidaFAIR at Meta在 meta.com 的电子邮件经过验证
Daniel A. RobertsResearch Scientist @ OpenAI, Visiting Scientist @ MIT在 mit.edu 的电子邮件经过验证
Simon FoucartProfessor of Mathematics, Texas A&M University在 tamu.edu 的电子邮件经过验证
Ingrid DaubechiesDuke University在 math.duke.edu 的电子邮件经过验证
Mark SellkeAssistant Professor of Statistics, Harvard University在 fas.harvard.edu 的电子邮件经过验证
Peng ZhouUC Berkeley, Math Department在 berkeley.edu 的电子邮件经过验证
Yi SunAssistant Professor, UChicago Statistics在 statistics.uchicago.edu 的电子邮件经过验证
Zhangyang (Atlas) WangXTX Markets & University of Texas at Austin在 utexas.edu 的电子邮件经过验证
Wuyang ChenAssistant Professor, CS@Simon Fraser University在 sfu.ca 的电子邮件经过验证
Grigoris PaourisProfessor in Mathematics, Texas A&M University在 math.tamu.edu 的电子邮件经过验证
Erik LundbergFlorida Atlantic University在 fau.edu 的电子邮件经过验证
Leonid HaninIdaho State University在 isu.edu 的电子邮件经过验证

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Boris Hanin

Assistant Professor, Princeton ORFE

在 princeton.edu 的电子邮件经过验证 - 首页

probability mathematical physics deep learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Universal function approximation by deep neural nets with bounded width and relu activations B Hanin Mathematics 7 (10), 992, 2019	415	2019
Which neural net architectures give rise to exploding and vanishing gradients? B Hanin Advances in neural information processing systems 31, 2018	310	2018
The principles of deep learning theory DA Roberts, S Yaida, B Hanin Cambridge University Press, 2022	301	2022
Nonlinear Approximation and (Deep) Networks I Daubechies, R DeVore, S Foucart, B Hanin, G Petrova Constructive Approximation 55 (1), 127-172, 2022	279	2022
How to start training: The effect of initialization and architecture B Hanin, D Rolnick Advances in neural information processing systems 31, 2018	276	2018
Approximating continuous functions by relu nets of minimal width B Hanin, M Sellke arXiv preprint arXiv:1710.11278, 2017	239	2017
Complexity of linear regions in deep networks B Hanin, D Rolnick International Conference on Machine Learning, 2596-2604, 2019	231	2019
Deep relu networks have surprisingly few activation patterns B Hanin, D Rolnick Advances in neural information processing systems 32, 2019	231	2019
Neural network approximation R DeVore, B Hanin, G Petrova Acta Numerica 30, 327-444, 2021	201	2021
Finite depth and width corrections to the neural tangent kernel B Hanin, M Nica arXiv preprint arXiv:1909.05989, 2019	161	2019
Products of many large random matrices and gradients in deep neural networks B Hanin, M Nica Communications in Mathematical Physics 376 (1), 287-322, 2020	79	2020
Scaling limit for the kernel of the spectral projector and remainder estimates in the pointwise Weyl law Y Canzani, B Hanin Analysis & PDE 8 (7), 1707-1731, 2015	45	2015
Random neural networks in the infinite width limit as Gaussian processes B Hanin The Annals of Applied Probability 33 (6A), 4798-4819, 2023	38	2023
Local universality for zeros and critical points of monochromatic random waves Y Canzani, B Hanin Communications in Mathematical Physics 378 (3), 1677-1712, 2020	31	2020
Correlations and pairing between zeros and critical points of Gaussian random polynomials B Hanin International Mathematics Research Notices 2015 (2), 381-421, 2015	31	2015
Pairing of zeros and critical points for random polynomials B Hanin	28	2017
Correlation functions in random fully connected neural networks at finite width B Hanin arXiv preprint arXiv:2204.01058, 2022	25	2022
Nodal sets of random eigenfunctions for the isotropic harmonic oscillator B Hanin, S Zelditch, P Zhou International Mathematics Research Notices 2015 (13), 4813-4839, 2015	24	2015
Scaling Asymptotics for the Spectral Projector of the Laplacian Y Canzani, B Hanin The Journal of Geometric Analysis 28, 111-122, 2018	22	2018
How data augmentation affects optimization for linear regression B Hanin, Y Sun Advances in neural information processing systems 34, 8095-8105, 2021	21	2021

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