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Why does deep and cheap learning work so well?

29 August 2016

Papers citing "Why does deep and cheap learning work so well?"

50 / 203 papers shown

Title
Como funciona o Deep Learning M. Ponti G. B. P. D. Costa 98 14 0 20 Jun 2018
Continuous-variable quantum neural networks N. Killoran T. Bromley J. M. Arrazola Maria Schuld N. Quesada S. Lloyd GNN 147 402 0 18 Jun 2018
Learning Dynamics of Linear Denoising Autoencoders Arnu Pretorius Steve Kroon Herman Kamper AI4CE 159 28 0 14 Jun 2018
Interpreting Deep Learning: The Machine Learning Rorschach Test? Adam S. Charles AAML HAI AI4CE 170 9 0 01 Jun 2018
Mean Field Theory of Activation Functions in Deep Neural Networks M. Milletarí Thiparat Chotibut P. E. Trevisanutto 93 4 0 22 May 2018
Deep learning generalizes because the parameter-function map is biased towards simple functions Guillermo Valle Pérez Chico Q. Camargo A. Louis MLT AI4CE 382 253 0 22 May 2018
Opening the black box of deep learning Dian Lei Xiaoxiao Chen Jianfei Zhao AI4CE PINN 136 28 0 22 May 2018
Reconciled Polynomial Machine: A Unified Representation of Shallow and Deep Learning Models Jiawei Zhang Limeng Cui Fisher B. Gouza FAtt 45 0 0 19 May 2018
On Deep Ensemble Learning from a Function Approximation Perspective Jiawei Zhang Limeng Cui Fisher B. Gouza FedML 52 0 0 19 May 2018
Doing the impossible: Why neural networks can be trained at all Nathan Oken Hodas P. Stinis AI4CE 154 21 0 13 May 2018
Distribution-Aware Binarization of Neural Networks for Sketch Recognition Christian Schroeder de Witt Vishal Batchu Sri Aurobindo Munagala Rohit Gajawada A. Namboodiri MQ 185 5 0 09 Apr 2018
Deep Learning of the Nonlinear Schrödinger Equation in Fiber-Optic Communications Christian Hager H. Pfister 83 49 0 09 Apr 2018
The Loss Surface of XOR Artificial Neural Networks D. Mehta Xiaojun Zhao Edgar A. Bernal D. Wales 224 19 0 06 Apr 2018
Understanding Autoencoders with Information Theoretic Concepts Shujian Yu José C. Príncipe AI4CE 414 141 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 323 933 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 152 33 0 22 Mar 2018
Assessing Shape Bias Property of Convolutional Neural Networks Hossein Hosseini Baicen Xiao Mayoore S. Jaiswal Radha Poovendran 124 38 0 21 Mar 2018
Generalization and Expressivity for Deep NetsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018 Shao-Bo Lin 151 48 0 10 Mar 2018
A computational perspective of the role of Thalamus in cognitionNeural Computation (Neural Comput.), 2018 Nima Dehghani R. D. Wimmer LRM 133 27 0 02 Mar 2018
Neural Network Renormalization Group Shuo-Hui Li Lei Wang BDL DRL 211 136 0 08 Feb 2018
Deep Learning Works in Practice. But Does it Work in Theory? L. Hoang R. Guerraoui PINN 78 3 0 31 Jan 2018
Scale-invariant Feature Extraction of Neural Network and Renormalization Group Flow S. Iso Shotaro Shiba Sumito Yokoo OOD AI4CE 166 75 0 22 Jan 2018
Information Perspective to Probabilistic Modeling: Boltzmann Machines versus Born Machines Song Cheng J. Chen Lei Wang 209 105 0 12 Dec 2017
Linearly-Recurrent Autoencoder Networks for Learning Dynamics Samuel E. Otto C. Rowley AI4CE 191 364 0 04 Dec 2017
Provably efficient neural network representation for image classification Yichen Huang 126 4 0 13 Nov 2017
Compact Neural Networks based on the Multiscale Entanglement Renormalization Ansatz A. Hallam Edward Grant V. Stojevic Simone Severini A. Green 193 9 0 09 Nov 2017
What Really is Deep Learning Doing? Chuyu Xiong VLM OOD 55 5 0 06 Nov 2017
An efficient quantum algorithm for generative machine learning Xun Gao Zhengyu Zhang L. Duan 123 25 0 06 Nov 2017
Approximating Continuous Functions by ReLU Nets of Minimal Width Boris Hanin Mark Sellke 193 258 0 31 Oct 2017
How deep learning works --The geometry of deep learning Xiao Dong Jiasong Wu Ling Zhou GNN 159 9 0 30 Oct 2017
Tensor network language model V. Pestun Yiannis Vlassopoulos 210 36 0 27 Oct 2017
Stability and Generalization of Learning Algorithms that Converge to Global OptimaInternational Conference on Machine Learning (ICML), 2017 Zachary B. Charles Dimitris Papailiopoulos MLT 163 175 0 23 Oct 2017
Nonlinear Interference Mitigation via Deep Neural Networks Christian Hager H. Pfister 112 146 0 17 Oct 2017
Calligraphic Stylisation Learning with a Physiologically Plausible Model of Movement and Recurrent Neural Networks Daniel Berio Memo Akten F. Leymarie M. Grierson R. Plamondon GAN 102 15 0 24 Sep 2017
A Computer Composes A Fabled Problem: Four Knights vs. Queen Azlan Iqbal 45 0 0 04 Sep 2017
Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives A. Cichocki Anh-Huy Phan Qibin Zhao Namgil Lee Ivan Oseledets Masashi Sugiyama Danilo P. Mandic 199 317 0 30 Aug 2017
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations Boris Hanin 314 374 0 09 Aug 2017
Language Design as Information Renormalization Ángel J. Gallego Roman Orus 226 21 0 04 Aug 2017
On the Importance of Consistency in Training Deep Neural Networks Chengxi Ye Yezhou Yang Cornelia Fermuller Yiannis Aloimonos 69 12 0 02 Aug 2017
Do Neural Nets Learn Statistical Laws behind Natural Language? Shuntaro Takahashi Kumiko Tanaka-Ishii 171 31 0 16 Jul 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Damien Scieur TDI 489 2,018 0 16 Jun 2017
The power of deeper networks for expressing natural functions David Rolnick Max Tegmark 215 185 0 16 May 2017
Mutual Information, Neural Networks and the Renormalization Group M. Koch-Janusz Zohar Ringel DRL AI4CE 178 186 0 20 Apr 2017
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design Yoav Levine David Yakira Nadav Cohen Amnon Shashua 223 131 0 05 Apr 2017
Design of the Artificial: lessons from the biological roots of general intelligence Nima Dehghani AI4CE 49 2 0 07 Mar 2017
Bayesian Boolean Matrix FactorisationInternational Conference on Machine Learning (ICML), 2017 Tammo Rukat Chris C. Holmes Michalis K. Titsias C. Yau 181 34 0 20 Feb 2017
Deep learning and the Schrödinger equation Kyle Mills M. Spanner Isaac Tamblyn 177 145 0 05 Feb 2017
Equivalence of restricted Boltzmann machines and tensor network states Martín Arjovsky Song Cheng Haidong Xie Léon Bottou Tao Xiang 194 234 0 17 Jan 2017
The Upper Bound on Knots in Neural Networks Kevin K. Chen 96 15 0 29 Nov 2016
Local minima in training of neural networks G. Swirszcz Wojciech M. Czarnecki Razvan Pascanu ODL 157 78 0 19 Nov 2016