An exact mapping between the Variational Renormalization Group and Deep Learning

14 October 2014

Papers citing "An exact mapping between the Variational Renormalization Group and Deep Learning"

50 / 102 papers shown

Title
Is Deep Learning a Renormalization Group Flow? E. Koch R. Koch Ling Cheng OOD AI4CE 33 5 0 12 Jun 2019
On the descriptive power of Neural-Networks as constrained Tensor Networks with exponentially large bond dimension M. Collura L. Dell’Anna Timo Felser S. Montangero 30 18 0 27 May 2019
Variational approach to unsupervised learning S. Shah PINN SSL 16 4 0 24 Apr 2019
Tree Tensor Networks for Generative Modeling Song Cheng Lei Wang Tao Xiang Pan Zhang 105 131 0 08 Jan 2019
Dreaming neural networks: rigorous results E. Agliari Francesco Alemanno Adriano Barra A. Fachechi CLL 51 25 0 21 Dec 2018
Measure, Manifold, Learning, and Optimization: A Theory Of Neural Networks Shuai Li 93 2 0 30 Nov 2018
Symmetry constrained machine learning D. Bergman 55 12 0 16 Nov 2018
Dreaming neural networks: forgetting spurious memories and reinforcing pure ones A. Fachechi E. Agliari Adriano Barra CLL 65 55 0 29 Oct 2018
A theoretical framework for deep locally connected ReLU network Yuandong Tian PINN 61 10 0 28 Sep 2018
Fuzzy Logic Interpretation of Quadratic Networks Fenglei Fan Ge Wang 62 7 0 04 Jul 2018
Interpreting Deep Learning: The Machine Learning Rorschach Test? Adam S. Charles AAML HAI AI4CE 95 9 0 01 Jun 2018
Mean Field Theory of Activation Functions in Deep Neural Networks M. Milletarí Thiparat Chotibut P. E. Trevisanutto 30 4 0 22 May 2018
Opening the black box of deep learning Dian Lei Xiaoxiao Chen Jianfei Zhao AI4CE PINN 56 27 0 22 May 2018
Doing the impossible: Why neural networks can be trained at all Nathan Oken Hodas P. Stinis AI4CE 42 20 0 13 May 2018
Understanding Autoencoders with Information Theoretic Concepts Shujian Yu José C. Príncipe AI4CE 129 134 0 30 Mar 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 121 880 0 23 Mar 2018
Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks P. Stinis Tobias J. Hagge A. Tartakovsky Enoch Yeung GAN AI4CE 77 33 0 22 Mar 2018
Vulnerability of Deep Learning R. Kenway AAML OOD 23 5 0 16 Mar 2018
Neural Network Renormalization Group Shuo-Hui Li Lei Wang BDL DRL 97 125 0 08 Feb 2018
Scale-invariant Feature Extraction of Neural Network and Renormalization Group Flow S. Iso Shotaro Shiba Sumito Yokoo OOD AI4CE 75 71 0 22 Jan 2018
Learning Relevant Features of Data with Multi-scale Tensor Networks Tayssir Doghri 120 138 0 31 Dec 2017
A trans-disciplinary review of deep learning research for water resources scientists Chaopeng Shen AI4CE 216 699 0 06 Dec 2017
Compact Neural Networks based on the Multiscale Entanglement Renormalization Ansatz A. Hallam Edward Grant V. Stojevic Simone Severini A. Green 57 9 0 09 Nov 2017
What Really is Deep Learning Doing? Chuyu Xiong VLM OOD 18 5 0 06 Nov 2017
Tensor network language model V. Pestun Yiannis Vlassopoulos 135 36 0 27 Oct 2017
What is the Machine Learning? Spencer Chang Timothy Cohen B. Ostdiek 29 38 0 28 Sep 2017
$Machine learning \& artificial intelligence in the quantum domain$ Machine learning \& artificial intelligence in the quantum domain Vedran Dunjko Hans J. Briegel 68 347 0 08 Sep 2017
Deep Learning the Ising Model Near Criticality A. Morningstar R. Melko AI4CE 66 86 0 15 Aug 2017
Between Homomorphic Signal Processing and Deep Neural Networks: Constructing Deep Algorithms for Polyphonic Music Transcription Li Su 46 21 0 26 Jun 2017
Criticality & Deep Learning II: Momentum Renormalisation Group D. Oprisa Peter Toth AI4CE 46 6 0 31 May 2017
Towards meaningful physics from generative models M. Cristoforetti Giuseppe Jurman Andrea I. Nardelli Cesare Furlanello OOD DRL AI4CE 49 17 0 26 May 2017
Mutual Information, Neural Networks and the Renormalization Group M. Koch-Janusz Zohar Ringel DRL AI4CE 93 176 0 20 Apr 2017
Unsupervised prototype learning in an associative-memory network Huiling Zhen Shang-Nan Wang Haijun Zhou SSL 29 1 0 10 Apr 2017
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design Yoav Levine David Yakira Nadav Cohen Amnon Shashua 121 126 0 05 Apr 2017
Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders S. J. Wetzel SSL DRL 50 318 0 07 Mar 2017
Equivalence of restricted Boltzmann machines and tensor network states Martín Arjovsky Song Cheng Haidong Xie Léon Bottou Tao Xiang 106 225 0 17 Jan 2017
Quantum Machine Learning Jacob Biamonte P. Wittek Nicola Pancotti Patrick Rebentrost N. Wiebe S. Lloyd 81 2,045 0 28 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 826 3,303 0 24 Nov 2016
Inferring low-dimensional microstructure representations using convolutional neural networks Nicholas Lubbers T. Lookman K. Barros 57 109 0 08 Nov 2016
Multilevel Anomaly Detection for Mixed Data Kien Do T. Tran Svetha Venkatesh 20 3 0 20 Oct 2016
A Perspective on Deep Imaging Ge Wang OOD 70 392 0 10 Sep 2016
Why does deep and cheap learning work so well? Henry W. Lin Max Tegmark David Rolnick 129 610 0 29 Aug 2016
Supervised Learning with Quantum-Inspired Tensor Networks E. Stoudenmire D. Schwab SSL 66 165 0 18 May 2016
Flow of Information in Feed-Forward Deep Neural Networks P. Khadivi Ravi Tandon Naren Ramakrishnan HAI 62 18 0 20 Mar 2016
PCANet: An energy perspective Jiasong Wu Shijie Qiu Youyong Kong Longyu Jiang L. Senhadji H. Shu 18 19 0 03 Mar 2016
A Deep Learning Approach to Unsupervised Ensemble Learning Uri Shaham Xiuyuan Cheng Omer Dror Ariel Jaffe B. Nadler Joseph T. Chang Y. Kluger UQCV 80 35 0 06 Feb 2016
Efficient algorithms for topological inference on random graphs I. Teodorescu Razvan Teodorescu Pranav I. Warman 18 0 0 31 Dec 2015
Provable approximation properties for deep neural networks Uri Shaham A. Cloninger Ronald R. Coifman 192 231 0 24 Sep 2015
A Probabilistic Theory of Deep Learning Ankit B. Patel M. T. Nguyen Richard G. Baraniuk BDL OOD UQCV 91 89 0 02 Apr 2015
A mathematical motivation for complex-valued convolutional networks Joan Bruna Soumith Chintala Yann LeCun Serkan Piantino Arthur Szlam M. Tygert 128 104 0 11 Mar 2015