Title
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Learning Lattice Quantum Field Theories with Equivariant Continuous Flows Mathis Gerdes P. D. Haan Corrado Rainone Roberto Bondesan Miranda C. N. Cheng AI4CE 77 41 0 01 Jul 2022
Flow-based density of states for complex actions J. Pawlowski Julian M. Urban 58 10 0 02 Mar 2022
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Stochastic normalizing flows as non-equilibrium transformations M. Caselle E. Cellini A. Nada M. Panero 84 35 0 21 Jan 2022
LeapfrogLayers: A Trainable Framework for Effective Topological Sampling Sam Foreman Xiao-Yong Jin James C. Osborn 44 9 0 02 Dec 2021
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows P. D. Haan Corrado Rainone Miranda C. N. Cheng Roberto Bondesan AI4CE 71 35 0 06 Oct 2021
Flow-based sampling for fermionic lattice field theories M. S. Albergo G. Kanwar S. Racanière Danilo Jimenez Rezende Julian M. Urban D. Boyda Kyle Cranmer D. Hackett P. Shanahan AI4CE 79 43 0 10 Jun 2021
Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks Dian Wu R. Rossi Giuseppe Carleo 86 29 0 12 May 2021
Deep Learning Hamiltonian Monte Carlo Sam Foreman Xiao-Yong Jin James C. Osborn 45 16 0 07 May 2021
Annealed Flow Transport Monte Carlo Michael Arbel A. G. Matthews Arnaud Doucet 91 78 0 15 Feb 2021
Introduction to Normalizing Flows for Lattice Field Theory M. S. Albergo D. Boyda D. Hackett G. Kanwar Kyle Cranmer S. Racanière Danilo Jimenez Rezende P. Shanahan AI4CE 79 58 0 20 Jan 2021
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 190 98 0 10 Dec 2020
Sampling using $SU(N)$ gauge equivariant flows D. Boyda G. Kanwar S. Racanière Danilo Jimenez Rezende M. S. Albergo Kyle Cranmer D. Hackett P. Shanahan 84 129 0 12 Aug 2020
Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models K. Nicoli Christopher J. Anders L. Funcke T. Hartung K. Jansen Pan Kessel Shinichi Nakajima Paolo Stornati AI4CE 53 3 0 14 Jul 2020
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows Didrik Nielsen P. Jaini Emiel Hoogeboom Ole Winther Max Welling TPM BDL DRL 75 92 0 06 Jul 2020
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Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 908 42,520 0 28 May 2020
Extending machine learning classification capabilities with histogram reweighting Dimitrios Bachtis Gert Aarts B. Lucini 50 21 0 29 Apr 2020
Equivariant flow-based sampling for lattice gauge theory G. Kanwar M. S. Albergo D. Boyda Kyle Cranmer D. Hackett S. Racanière Danilo Jimenez Rezende P. Shanahan AI4CE 66 176 0 13 Mar 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 146 185 0 16 Feb 2020
Normalizing Flows on Tori and Spheres Danilo Jimenez Rezende George Papamakarios S. Racanière M. S. Albergo G. Kanwar P. Shanahan Kyle Cranmer TPM 91 157 0 06 Feb 2020
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Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 194 778 0 10 Jun 2019
Flow-based generative models for Markov chain Monte Carlo in lattice field theory M. S. Albergo G. Kanwar P. Shanahan AI4CE 105 219 0 26 Apr 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 73 108 0 09 Mar 2019
Solving Statistical Mechanics Using Variational Autoregressive Networks Dian Wu Lei Wang Pan Zhang 114 186 0 27 Sep 2018
Monge-Ampère Flow for Generative Modeling Linfeng Zhang E. Weinan Lei Wang DRL 92 63 0 26 Sep 2018
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Horovod: fast and easy distributed deep learning in TensorFlow Alexander Sergeev Mike Del Balso 102 1,222 0 15 Feb 2018
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Towards reduction of autocorrelation in HMC by machine learning A. Tanaka A. Tomiya 49 27 0 11 Dec 2017
Generalizing Hamiltonian Monte Carlo with Neural Networks Daniel Levy Matthew D. Hoffman Jascha Narain Sohl-Dickstein BDL 77 130 0 25 Nov 2017
Don't Decay the Learning Rate, Increase the Batch Size Samuel L. Smith Pieter-Jan Kindermans Chris Ying Quoc V. Le ODL 124 996 0 01 Nov 2017
A-NICE-MC: Adversarial Training for MCMC Jiaming Song Shengjia Zhao Stefano Ermon BDL OOD 113 110 0 23 Jun 2017
Accelerate Monte Carlo Simulations with Restricted Boltzmann Machines Li Huang Lei Wang AI4CE 64 199 0 10 Oct 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 277 3,723 0 26 May 2016
A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation Qiang Liu Jason D. Lee Michael I. Jordan 116 486 0 10 Feb 2016
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 324 4,198 0 21 May 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 358 18,661 0 06 Feb 2015
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NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 146 2,269 0 30 Oct 2014
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 165 6,635 0 22 Dec 2012