Mutual Information, Neural Networks and the Renormalization Group

20 April 2017

Papers citing "Mutual Information, Neural Networks and the Renormalization Group"

50 / 52 papers shown

Title
A Two-Phase Perspective on Deep Learning Dynamics Robert de Mello Koch Animik Ghosh 41 0 0 17 Apr 2025
Data augmentation using diffusion models to enhance inverse Ising inference Yechan Lim Sangwon Lee Junghyo Jo DiffM 53 0 0 13 Mar 2025
Multilevel Generative Samplers for Investigating Critical Phenomena Ankur Singha E. Cellini K. Nicoli K. Jansen Stefan Kühn Shinichi Nakajima 64 1 0 11 Mar 2025
Surveying the space of descriptions of a composite system with machine learning Kieran A. Murphy Yujing Zhang D. Bassett 84 0 0 27 Nov 2024
GUD: Generation with Unified Diffusion Mathis Gerdes Max Welling Miranda C. N. Cheng DiffM 37 1 0 03 Oct 2024
MS $^3$ D: A RG Flow-Based Regularization for GAN Training with Limited Data Jian Wang Xin Lan Yuxin Tian Jiancheng Lv AI4CE 38 1 0 20 Aug 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 68 1 0 27 May 2024
Wilsonian Renormalization of Neural Network Gaussian Processes Jessica N. Howard Ro Jefferson Anindita Maiti Zohar Ringel BDL 80 3 0 09 May 2024
Tensor networks for interpretable and efficient quantum-inspired machine learning Shirli Ran Gang Su 45 7 0 19 Nov 2023
Renormalizing Diffusion Models Jordan S. Cotler Semon Rezchikov DiffM AI4CE 37 11 0 23 Aug 2023
Information decomposition in complex systems via machine learning Kieran A. Murphy Danielle Bassett 36 9 0 10 Jul 2023
Three Learning Stages and Accuracy-Efficiency Tradeoff of Restricted Boltzmann Machines Lennart Dabelow Masahito Ueda 38 11 0 02 Sep 2022
NFDLM: A Lightweight Network Flow based Deep Learning Model for DDoS Attack Detection in IoT Domains Kumar Saurabh T. kumar Uphar Singh O. P. Vyas R. Khondoker 17 11 0 15 Jul 2022
Boundary between noise and information applied to filtering neural network weight matrices Max Staats M. Thamm B. Rosenow 23 3 0 08 Jun 2022
Categorical Representation Learning and RG flow operators for algorithmic classifiers A. Sheshmani Yi-Zhuang You Wenbo Fu A. Azizi AI4CE 14 1 0 15 Mar 2022
Learning entanglement breakdown as a phase transition by confusion M. A. Gavreev A. S. Mastiukova E. Kiktenko A. Fedorov 24 9 0 01 Feb 2022
Neural Information Squeezer for Causal Emergence Jiang Zhang Kaiwei Liu CML 30 14 0 25 Jan 2022
Differentiable Programming of Isometric Tensor Networks Chenhua Geng Hong-Ye Hu Yijian Zou 31 10 0 08 Oct 2021
Universality of Winning Tickets: A Renormalization Group Perspective William T. Redman Tianlong Chen Zhangyang Wang Akshunna S. Dogra UQCV 62 7 0 07 Oct 2021
Nonperturbative renormalization for the neural network-QFT correspondence Harold Erbin Vincent Lahoche D. O. Samary 41 30 0 03 Aug 2021
Towards quantifying information flows: relative entropy in deep neural networks and the renormalization group J. Erdmenger Kevin T. Grosvenor R. Jefferson 54 17 0 14 Jul 2021
The Autodidactic Universe S. Alexander W. Cunningham J. Lanier L. Smolin S. Stanojevic M. Toomey D. Wecker AI4CE 10 20 0 29 Mar 2021
Tensor networks and efficient descriptions of classical data Sirui Lu Márton Kanász-Nagy I. Kukuljan J. I. Cirac 24 24 0 11 Mar 2021
Adding machine learning within Hamiltonians: Renormalization group transformations, symmetry breaking and restoration Dimitrios Bachtis Gert Aarts B. Lucini AI4CE 23 19 0 30 Sep 2020
RG-Flow: A hierarchical and explainable flow model based on renormalization group and sparse prior Hong-Ye Hu Dian Wu Yi-Zhuang You Bruno A. Olshausen Yubei Chen BDL DRL 17 15 0 30 Sep 2020
Maximum Multiscale Entropy and Neural Network Regularization Amir-Reza Asadi Emmanuel Abbe 23 1 0 25 Jun 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity S. Udrescu A. Tan Jiahai Feng Orisvaldo Neto Tailin Wu Max Tegmark 8 183 0 18 Jun 2020
Restricted Boltzmann Machine Flows and The Critical Temperature of Ising models R. Veiga R. Vicente AI4CE 8 5 0 17 Jun 2020
Machine Learning for Condensed Matter Physics Edwin Bedolla L. C. Padierna R. Castañeda-Priego AI4CE 20 66 0 28 May 2020
Symbolic Pregression: Discovering Physical Laws from Distorted Video S. Udrescu Max Tegmark 21 40 0 19 May 2020
Boosting on the shoulders of giants in quantum device calibration A. Wozniakowski Jayne Thompson M. Gu F. Binder 16 3 0 13 May 2020
Probing Criticality in Quantum Spin Chains with Neural Networks A. Berezutskii M. Beketov D. Yudin Z. Zimborás J Biamonte AI4CE 11 9 0 05 May 2020
Renormalized Mutual Information for Artificial Scientific Discovery Leopoldo Sarra A. Aiello F. Marquardt 11 4 0 04 May 2020
Learning entropy production via neural networks Dong-Kyum Kim Youngkyoung Bae Sangyun Lee Hawoong Jeong 11 38 0 09 Mar 2020
Short sighted deep learning R. Koch Anita de Mello Koch Nicholas Kastanos Ling Cheng 22 8 0 07 Feb 2020
Learning the Ising Model with Generative Neural Networks Francesco DÁngelo Lucas Böttcher AI4CE 16 28 0 15 Jan 2020
'Place-cell' emergence and learning of invariant data with restricted Boltzmann machines: breaking and dynamical restoration of continuous symmetries in the weight space Moshir Harsh J. Tubiana Simona Cocco R. Monasson 11 14 0 30 Dec 2019
Self-regularizing restricted Boltzmann machines Orestis Loukas 11 2 0 09 Dec 2019
The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos? Gege Zhang Gang-cheng Li Ningwei Shen Weidong Zhang 22 6 0 11 Oct 2019
The many faces of deep learning Raul Vicente FedML AI4CE 19 0 0 25 Aug 2019
Learning a Local Symmetry with Neural-Networks A. Decelle V. Martín-Mayor Beatriz Seoane 11 12 0 16 Apr 2019
Revealing quantum chaos with machine learning Y. Kharkov V. E. Sotskov A. A. Karazeev E. Kiktenko A. Fedorov AI4CE 27 27 0 25 Feb 2019
Thermodynamics and Feature Extraction by Machine Learning S. Funai D. Giataganas DRL AI4CE 16 34 0 18 Oct 2018
Discovering physical concepts with neural networks Raban Iten Tony Metger H. Wilming L. D. Rio R. Renner PINN AI4CE 19 385 0 26 Jul 2018
Mean Field Theory of Activation Functions in Deep Neural Networks M. Milletarí Thiparat Chotibut P. E. Trevisanutto 12 4 0 22 May 2018
Opening the black box of deep learning Dian Lei Xiaoxiao Chen Jianfei Zhao AI4CE PINN 13 26 0 22 May 2018
A high-bias, low-variance introduction to Machine Learning for physicists Pankaj Mehta Marin Bukov Ching-Hao Wang A. G. Day C. Richardson Charles K. Fisher D. Schwab AI4CE 26 867 0 23 Mar 2018
Neural Network Renormalization Group Shuo-Hui Li Lei Wang BDL DRL 31 126 0 08 Feb 2018
Scale-invariant Feature Extraction of Neural Network and Renormalization Group Flow S. Iso Shotaro Shiba Sumito Yokoo OOD AI4CE 35 70 0 22 Jan 2018
Information Perspective to Probabilistic Modeling: Boltzmann Machines versus Born Machines Song Cheng J. Chen Lei Wang 24 101 0 12 Dec 2017