Zohar Ringel

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 16

Top Topics

Learning Curves

Gaussian Processes

Preference Learning

Top Venues

Publications

Noa Rubin, Inbar Seroussi, Zohar Ringel
Grokking as a First Order Phase Transition in Two Layer Networks. ICLR (2024)
Itay Lavie, Zohar Ringel
Symmetric Kernels with Non-Symmetric Data: A Data-Agnostic Learnability Bound. CoRR (2024)
Itay Lavie, Guy Gur-Ari, Zohar Ringel
Towards Understanding Inductive Bias in Transformers: A View From Infinity. CoRR (2024)
Jessica N. Howard, Ro Jefferson, Anindita Maiti, Zohar Ringel
Wilsonian Renormalization of Neural Network Gaussian Processes. 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)