Mean-field inference methods for neural networks

3 November 2019

Papers citing "Mean-field inference methods for neural networks"

50 / 78 papers shown

Title
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 312 10,591 0 17 Feb 2020
Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning A. Abbara Benjamin Aubin Florent Krzakala Lenka Zdeborová 132 13 0 05 Dec 2019
Large Deviation Analysis of Function Sensitivity in Random Deep Neural Networks Bo Li D. Saad 44 12 0 13 Oct 2019
Modelling the influence of data structure on learning in neural networks: the hidden manifold model Sebastian Goldt M. Mézard Florent Krzakala Lenka Zdeborová BDL 57 51 0 25 Sep 2019
Disentangling feature and lazy training in deep neural networks Mario Geiger S. Spigler Arthur Jacot Matthieu Wyart 95 17 0 19 Jun 2019
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup Sebastian Goldt Madhu S. Advani Andrew M. Saxe Florent Krzakala Lenka Zdeborová MLT 98 143 0 18 Jun 2019
The spiked matrix model with generative priors Benjamin Aubin Bruno Loureiro Antoine Maillard Florent Krzakala Lenka Zdeborová 55 53 0 29 May 2019
Generalized Approximate Survey Propagation for High-Dimensional Estimation Luca Saglietti Yue M. Lu Carlo Lucibello 53 11 0 13 May 2019
Depth Separations in Neural Networks: What is Actually Being Separated? Itay Safran Ronen Eldan Ohad Shamir MDE 51 36 0 15 Apr 2019
Asymptotics of MAP Inference in Deep Networks Parthe Pandit Mojtaba Sahraee S. Rangan A. Fletcher 54 21 0 01 Mar 2019
A Mean Field Theory of Batch Normalization Greg Yang Jeffrey Pennington Vinay Rao Jascha Narain Sohl-Dickstein S. Schoenholz 60 178 0 21 Feb 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 178 1,097 0 18 Feb 2019
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit Song Mei Theodor Misiakiewicz Andrea Montanari MLT 68 278 0 16 Feb 2019
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs D. Gilboa B. Chang Minmin Chen Greg Yang S. Schoenholz Ed H. Chi Jeffrey Pennington 68 42 0 25 Jan 2019
Memory-free dynamics for the TAP equations of Ising models with arbitrary rotation invariant ensembles of random coupling matrices Burak Çakmak Manfred Opper 39 20 0 24 Jan 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks Umut Simsekli Levent Sagun Mert Gurbuzbalaban 82 247 0 18 Jan 2019
Deep Neural Network Approximation Theory Dennis Elbrächter Dmytro Perekrestenko Philipp Grohs Helmut Bölcskei 47 210 0 08 Jan 2019
Scaling description of generalization with number of parameters in deep learning Mario Geiger Arthur Jacot S. Spigler Franck Gabriel Levent Sagun Stéphane dÁscoli Giulio Biroli Clément Hongler Matthieu Wyart 76 195 0 06 Jan 2019
Mean-field theory of graph neural networks in graph partitioning T. Kawamoto Masashi Tsubaki T. Obuchi 67 58 0 29 Oct 2018
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes Roman Novak Lechao Xiao Jaehoon Lee Yasaman Bahri Greg Yang Jiri Hron Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 54 308 0 11 Oct 2018
Phase Retrieval Under a Generative Prior Paul Hand Oscar Leong V. Voroninski 55 189 0 11 Jul 2018
Approximate Survey Propagation for Statistical Inference F. Antenucci Florent Krzakala Pierfrancesco Urbani Lenka Zdeborová 64 21 0 03 Jul 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 234 3,191 0 20 Jun 2018
The committee machine: Computational to statistical gaps in learning a two-layers neural network Benjamin Aubin Antoine Maillard Jean Barbier Florent Krzakala N. Macris Lenka Zdeborová 67 106 0 14 Jun 2018
Assessing Generative Models via Precision and Recall Mehdi S. M. Sajjadi Olivier Bachem Mario Lucic Olivier Bousquet Sylvain Gelly EGVM 73 575 0 31 May 2018
Entropy and mutual information in models of deep neural networks Marylou Gabrié Andre Manoel Clément Luneau Jean Barbier N. Macris Florent Krzakala Lenka Zdeborová 61 180 0 24 May 2018
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport Lénaïc Chizat Francis R. Bach OT 181 734 0 24 May 2018
A Solvable High-Dimensional Model of GAN Chuang Wang Hong Hu Yue M. Lu 45 16 0 22 May 2018
Glassy nature of the hard phase in inference problems F. Antenucci S. Franz Pierfrancesco Urbani Lenka Zdeborová 36 29 0 15 May 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 81 857 0 18 Apr 2018
SUNLayer: Stable denoising with generative networks D. Mixon Soledad Villar 48 21 0 25 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 79 873 0 23 Mar 2018
Comparing Dynamics: Deep Neural Networks versus Glassy Systems Marco Baity-Jesi Levent Sagun Mario Geiger S. Spigler Gerard Ben Arous C. Cammarota Yann LeCun Matthieu Wyart Giulio Biroli AI4CE 92 114 0 19 Mar 2018
Thermodynamics of Restricted Boltzmann Machines and related learning dynamics A. Decelle G. Fissore Cyril Furtlehner AI4CE 72 42 0 05 Mar 2018
Mathematics of Deep Learning René Vidal Joan Bruna Raja Giryes Stefano Soatto OOD 56 120 0 13 Dec 2017
Three Factors Influencing Minima in SGD Stanislaw Jastrzebski Zachary Kenton Devansh Arpit Nicolas Ballas Asja Fischer Yoshua Bengio Amos Storkey 76 463 0 13 Nov 2017
On the role of synaptic stochasticity in training low-precision neural networks Carlo Baldassi Federica Gerace H. Kappen Carlo Lucibello Luca Saglietti Enzo Tartaglione R. Zecchina 39 23 0 26 Oct 2017
Classification and Geometry of General Perceptual Manifolds SueYeon Chung Daniel D. Lee H. Sompolinsky 52 154 0 17 Oct 2017
High-dimensional dynamics of generalization error in neural networks Madhu S. Advani Andrew M. Saxe AI4CE 128 469 0 10 Oct 2017
Exploring the Function Space of Deep-Learning Machines Yue Liu D. Saad PINN 47 25 0 04 Aug 2017
Inference in Deep Networks in High Dimensions A. Fletcher S. Rangan BDL 103 69 0 20 Jun 2017
Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing Andre Manoel Florent Krzakala Eric W. Tramel Lenka Zdeborová 56 13 0 02 Jun 2017
Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk Paul Hand V. Voroninski UQCV 109 138 0 22 May 2017
Compressed Sensing using Generative Models Ashish Bora A. Jalal Eric Price A. Dimakis 120 808 0 09 Mar 2017
Opening the Black Box of Deep Neural Networks via Information Ravid Shwartz-Ziv Naftali Tishby AI4CE 98 1,407 0 02 Mar 2017
Depth Separation for Neural Networks Amit Daniely MDE 37 74 0 27 Feb 2017
Phase Diagram of Restricted Boltzmann Machines and Generalised Hopfield Networks with Arbitrary Priors Adriano Barra G. Genovese Peter Sollich Daniele Tantari 43 69 0 20 Feb 2017
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines Eric W. Tramel Marylou Gabrié Andre Manoel F. Caltagirone Florent Krzakala AI4CE 51 32 0 10 Feb 2017
Multi-Layer Generalized Linear Estimation Andre Manoel Florent Krzakala M. Mézard Lenka Zdeborová 42 54 0 24 Jan 2017
Constrained Low-rank Matrix Estimation: Phase Transitions, Approximate Message Passing and Applications T. Lesieur Florent Krzakala Lenka Zdeborová 109 127 0 03 Jan 2017