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Zohar Ringel
Publication Activity (10 Years)
Years Active: 2017-2024
Publications (10 Years): 13
Top Topics
Learning Curves
Davis Putnam
Gaussian Processes
Neural Network
Top Venues
CoRR
ICLR (Poster)
NeurIPS
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Publications
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Itay Lavie
,
Guy Gur-Ari
,
Zohar Ringel
Towards Understanding Inductive Bias in Transformers: A View From Infinity.
CoRR
(2024)
Noa Rubin
,
Inbar Seroussi
,
Zohar Ringel
Droplets of Good Representations: Grokking as a First Order Phase Transition in Two Layer Networks.
CoRR
(2023)
Inbar Seroussi
,
Asaf Miron
,
Zohar Ringel
Spectral-Bias and Kernel-Task Alignment in Physically Informed Neural Networks.
CoRR
(2023)
Inbar Seroussi
,
Alexander A. Alemi
,
Moritz Helias
,
Zohar Ringel
Speed Limits for Deep Learning.
CoRR
(2023)
Gadi Naveh
,
Zohar Ringel
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs.
CoRR
(2021)
Inbar Seroussi
,
Zohar Ringel
Separation of scales and a thermodynamic description of feature learning in some CNNs.
CoRR
(2021)
Gadi Naveh
,
Zohar Ringel
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs.
NeurIPS
(2021)
Amit Gordon
,
Aditya Banerjee
,
Maciej Koch-Janusz
,
Zohar Ringel
Relevance in the Renormalization Group and in Information Theory.
CoRR
(2020)
Gadi Naveh
,
Oded Ben-David
,
Haim Sompolinsky
,
Zohar Ringel
Predicting the outputs of finite networks trained with noisy gradients.
CoRR
(2020)
Omry Cohen
,
Or Malka
,
Zohar Ringel
Learning Curves for Deep Neural Networks: A Gaussian Field Theory Perspective.
CoRR
(2019)
Oded Ben-David
,
Zohar Ringel
The role of a layer in deep neural networks: a Gaussian Process perspective.
CoRR
(2019)
Zohar Ringel
,
Rodrigo Andrade de Bem
Critical Percolation as a Framework to Analyze the Training of Deep Networks.
ICLR (Poster)
(2018)
Maciej Koch-Janusz
,
Zohar Ringel
Mutual Information, Neural Networks and the Renormalization Group.
CoRR
(2017)