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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
Learning Fair Representations with Kolmogorov-Arnold Networks Amisha Priyadarshini Sergio Gago Masagué FaML 411 0 0 14 Nov 2025
Comparison of generalised additive models and neural networks in applications: A systematic review Jessica Doohan Lucas Kook Kevin Burke 56 0 0 28 Oct 2025
Symmetry and Generalisation in Neural Approximations of Renormalisation Transformations Cassidy Ashworth Pietro Lio Francesco Caso AI4CE 80 0 0 18 Oct 2025
Attention to Order: Transformers Discover Phase Transitions via Learnability Şener Özönder 68 0 0 08 Oct 2025
Multi-Agent Design Assistant for the Simulation of Inertial Fusion Energy Meir H. Shachar D. Sterbentz Harshitha Menon C. Jekel M. Giselle Fernández-Godino ... Kevin Korner Robert Rieben D. White William J. Schill Jonathan L. Belof AI4CE 135 0 0 02 Oct 2025
Latent Twins Matthias Chung Deepanshu Verma Max Collins Amit N. Subrahmanya Varuni Katti Sastry Vishwas Rao SyDa AI4CE 116 0 0 24 Sep 2025
Should We Always Train Models on Fine-Grained Classes? Davide Pirovano Federico Milanesio Michele Caselle Piero Fariselli Matteo Osella 68 0 0 05 Sep 2025
AI LLM Proof of Self-Consciousness and User-Specific Attractors Jeffrey Camlin 44 0 0 22 Aug 2025
On the creation of narrow AI: hierarchy and nonlocality of neural network skills Eric J. Michaud Asher Parker-Sartori Max Tegmark 366 2 0 21 May 2025
A Mathematical Philosophy of Explanations in Mechanistic Interpretability -- The Strange Science Part I.i Kola Ayonrinde Louis Jaburi MILM 438 3 0 01 May 2025
The Quantum LLM: Modeling Semantic Spaces with Quantum Principles Timo Aukusti Laine 114 1 0 13 Apr 2025
KAC: Kolmogorov-Arnold Classifier for Continual LearningComputer Vision and Pattern Recognition (CVPR), 2025 Yusong Hu Zichen Liang Fei Yang Qibin Hou Xialei Liu Ming-Ming Cheng CLL 275 5 0 27 Mar 2025
Multilevel Generative Samplers for Investigating Critical PhenomenaInternational Conference on Learning Representations (ICLR), 2025 Ankur Singha E. Cellini K. Nicoli K. Jansen Stefan Kühn Shinichi Nakajima 285 4 0 11 Mar 2025
Aligning Generalisation Between Humans and Machines Filip Ilievski Barbara Hammer F. V. Harmelen Benjamin Paassen S. Saralajew ... Vered Shwartz Gabriella Skitalinskaya Clemens Stachl Gido M. van de Ven T. Villmann 645 2 0 23 Nov 2024
Dynamic neuron approach to deep neural networks: Decoupling neurons for renormalization group analysis Donghee Lee Hye-Sung Lee Jaeok Yi 353 3 0 01 Oct 2024
MS $^3$ D: A RG Flow-Based Regularization for GAN Training with Limited DataInternational Conference on Machine Learning (ICML), 2024 Jian Wang Xin Lan Yuxin Tian Jiancheng Lv AI4CE 152 2 0 20 Aug 2024
KAN: Kolmogorov-Arnold Networks Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Soljacic Thomas Y. Hou Max Tegmark 868 1,133 0 30 Apr 2024
Extracting Formulae in Many-Valued Logic from Deep Neural NetworksIEEE Transactions on Signal Processing (IEEE TSP), 2024 Yani Zhang Helmut Bölcskei 124 0 0 22 Jan 2024
Deep Neural Networks for Automatic Speaker Recognition Do Not Learn Supra-Segmental Temporal FeaturesPattern Recognition Letters (PR), 2023 Daniel Neururer Volker Dellwo Thilo Stadelmann 214 3 0 01 Nov 2023
The Evolution of the Interplay Between Input Distributions and Linear Regions in Networks Xuan Qi Yi Wei 161 0 0 28 Oct 2023
A Hyperparameter Study for Quantum Kernel MethodsQuantum Machine Intelligence (QMI), 2023 Sebastian Egginger Alona Sakhnenko J. M. Lorenz 202 13 0 18 Oct 2023
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 254 1 0 13 Sep 2023
Scale-Preserving Automatic Concept Extraction (SPACE)Machine-mediated learning (ML), 2023 Andres Felipe Posada-Moreno Lukas Kreisköther T. Glander Sebastian Trimpe 93 1 0 11 Aug 2023
Iterative Magnitude Pruning as a Renormalisation Group: A Study in The Context of The Lottery Ticket Hypothesis Abu-Al Hassan 128 0 0 06 Aug 2023
Deep Convolutional Neural Networks with Zero-Padding: Feature Extraction and Learning Zhixiong Han Baichen Liu Shao-Bo Lin Ding-Xuan Zhou 133 6 0 30 Jul 2023
Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning V. Usatyuk Sergey Egorov Denis Sapozhnikov 277 3 0 28 Jul 2023
Deep neural networks have an inbuilt Occam's razorNature Communications (Nat. Commun.), 2023 Chris Mingard Henry Rees Guillermo Valle Pérez A. Louis UQCV BDL 240 28 0 13 Apr 2023
From Wide to Deep: Dimension Lifting Network for Parameter-efficient Knowledge Graph EmbeddingIEEE Transactions on Knowledge and Data Engineering (TKDE), 2023 Borui Cai Yong Xiang Longxiang Gao Di Wu Heng Zhang Jiongdao Jin Tom H. Luan 206 3 0 22 Mar 2023
Expressivity of Shallow and Deep Neural Networks for Polynomial Approximation Itai Shapira 92 0 0 06 Mar 2023
MOSAIC, acomparison framework for machine learning models Mattéo Papin Yann Beaujeault-Taudiere F. Magniette VLM 63 0 0 30 Jan 2023
A prediction and behavioural analysis of machine learning methods for modelling travel mode choiceTransportation Research Part C: Emerging Technologies (TRC), 2023 José Ángel Martín-Baos Julio Alberto López-Gómez Luis Rodriguez-Benitez T. Hillel Ricardo García-Ródenas 180 30 0 11 Jan 2023
Inference on Time Series Nonparametric Conditional Moment Restrictions Using General Sieves Xiaohong Chen Yuan Liao Weichen Wang 142 0 0 31 Dec 2022
Renormalization in the neural network-quantum field theory correspondence Harold Erbin Vincent Lahoche D. O. Samary 217 8 0 22 Dec 2022
Changes from Classical Statistics to Modern Statistics and Data Science Kai Zhang Shan-Yu Liu M. Xiong 231 1 0 30 Oct 2022
Hierarchical quantum circuit representations for neural architecture searchnpj Quantum Information (NQI), 2022 Matt Lourens I. Sinayskiy D. Park Carsten Blank Francesco Petruccione 252 15 0 26 Oct 2022
Deep Neural Networks as the Semi-classical Limit of Topological Quantum Neural Networks: The problem of generalisation A. Marcianò De-Wei Chen Filippo Fabrocini C. Fields M. Lulli Emanuele Zappala GNN 102 5 0 25 Oct 2022
Precision Machine Learning Eric J. Michaud Ziming Liu Max Tegmark 133 40 0 24 Oct 2022
When Expressivity Meets Trainability: Fewer than $n$ Neurons Can WorkNeural Information Processing Systems (NeurIPS), 2022 Jiawei Zhang Yushun Zhang Mingyi Hong Tian Ding Jianfeng Yao 271 10 0 21 Oct 2022
Why neural networks find simple solutions: the many regularizers of geometric complexityNeural Information Processing Systems (NeurIPS), 2022 Benoit Dherin Michael Munn M. Rosca David Barrett 276 41 0 27 Sep 2022
Three Learning Stages and Accuracy-Efficiency Tradeoff of Restricted Boltzmann MachinesNature Communications (Nat Commun), 2022 Lennart Dabelow Masahito Ueda 182 11 0 02 Sep 2022
Gaussian Process Surrogate Models for Neural NetworksConference on Uncertainty in Artificial Intelligence (UAI), 2022 Michael Y. Li Erin Grant Thomas Griffiths BDL SyDa 224 9 0 11 Aug 2022
Image sensing with multilayer, nonlinear optical neural networksNature Photonics (Nat. Photonics), 2022 Tianyu Wang Mandar M. Sohoni Logan G. Wright Martin M. Stein Shifan Ma Tatsuhiro Onodera Maxwell G. Anderson Peter L. McMahon 127 212 0 27 Jul 2022
Wavelet Conditional Renormalization GroupPhysical Review X (PRX), 2022 Tanguy Marchand M. Ozawa Giulio Biroli S. Mallat 106 21 0 11 Jul 2022
Advanced Transient Diagnostic with Ensemble Digital Twin Modeling Edward Chen Linyu Lin Truc-Nam Dinh 54 4 0 23 May 2022
Towards understanding deep learning with the natural clustering prior Simon Carbonnelle 144 0 0 15 Mar 2022
Categorical Representation Learning and RG flow operators for algorithmic classifiers A. Sheshmani Yi-Zhuang You Wenbo Fu A. Azizi AI4CE 57 4 0 15 Mar 2022
Identifying equivalent Calabi--Yau topologies: A discrete challenge from math and physics for machine learning Vishnu Jejjala W. Taylor Andrew P. Turner 241 8 0 15 Feb 2022
Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networks Shaun Li AI4CE 186 1 0 03 Jan 2022
Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation Jeffmin Lin Gil Goldshlager Lin Lin 181 29 0 07 Dec 2021
Error Bounds for a Matrix-Vector Product Approximation with Deep ReLU Neural Networks T. Getu 169 2 0 25 Nov 2021