Faster Eigenvector Computation via Shift-and-Invert Preconditioning

26 May 2016

Dan Garber

Laurent Dinh

Chi Jin

Jascha Narain Sohl-Dickstein

Papers citing "Faster Eigenvector Computation via Shift-and-Invert Preconditioning"

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Title
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 336 543 0 14 Aug 2018
Neural Importance Sampling Thomas Müller Brian McWilliams Fabrice Rousselle Markus Gross Jan Novák 280 403 0 11 Aug 2018
Unbiased Implicit Variational Inference Michalis K. Titsias Francisco J. R. Ruiz BDL 320 60 0 06 Aug 2018
A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling Zhijian Ou 229 15 0 05 Aug 2018
Likelihood-free inference with an improved cross-entropy estimator M. Stoye Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer FedML UQCV BDL 221 51 0 02 Aug 2018
Understanding and Improving Interpolation in Autoencoders via an Adversarial RegularizerInternational Conference on Learning Representations (ICLR), 2018 David Berthelot Colin Raffel Aurko Roy Ian Goodfellow 276 276 0 19 Jul 2018
ClariNet: Parallel Wave Generation in End-to-End Text-to-SpeechInternational Conference on Learning Representations (ICLR), 2018 Ming-Yu Liu Kainan Peng Jitong Chen 288 358 0 19 Jul 2018
Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions Tim Sainburg Marvin Thielk Brad Theilman Benjamin Migliori T. Gentner DRL GAN 236 55 0 17 Jul 2018
IntroVAE: Introspective Variational Autoencoders for Photographic Image SynthesisNeural Information Processing Systems (NeurIPS), 2018 Huaibo Huang Zhihang Li Ran He Zhenan Sun Tieniu Tan DRL 187 284 0 17 Jul 2018
Glow: Generative Flow with Invertible 1x1 ConvolutionsNeural Information Processing Systems (NeurIPS), 2018 Diederik P. Kingma Prafulla Dhariwal BDL DRL 699 3,394 0 09 Jul 2018
Resembled Generative Adversarial Networks: Two Domains with Similar AttributesBritish Machine Vision Conference (BMVC), 2018 Duhyeon Bang Hyunjung Shim GAN OOD 130 6 0 03 Jul 2018
Mixed batches and symmetric discriminators for GAN training Thomas Lucas Corentin Tallec Jakob Verbeek Yann Ollivier 153 38 0 19 Jun 2018
Deep State Space Models for Unconditional Word Generation Florian Schmidt Thomas Hofmann 142 16 0 12 Jun 2018
Meta-Learning for Stochastic Gradient MCMC Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato BDL 307 44 0 12 Jun 2018
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior L. Mosser O. Dubrule M. Blunt GAN AI4CE 233 222 0 10 Jun 2018
Implicit Policy for Reinforcement Learning Yunhao Tang Shipra Agrawal 183 14 0 10 Jun 2018
Randomized Value Functions via Multiplicative Normalizing Flows Ahmed Touati Harsh Satija Joshua Romoff Joelle Pineau Pascal Vincent 113 39 0 06 Jun 2018
Training Generative Reversible Networks R. Schirrmeister Patryk Chrabkaszcz Katharina Eggensperger T. Ball BDL GAN 172 8 0 05 Jun 2018
Backpropagation for Implicit Spectral Densities Aditya A. Ramesh Yann LeCun 104 10 0 01 Jun 2018
On GANs and GMMs Eitan Richardson Yair Weiss GAN 289 158 0 31 May 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 454 195 0 30 May 2018
Norm-Preservation: Why Residual Networks Can Become Extremely Deep? Alireza Zaeemzadeh Nazanin Rahnavard M. Shah 139 74 0 18 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 770 414 0 18 May 2018
Replicating Active Appearance Model by Generator Network Tian Han Jiawen Wu Ying Nian Wu CVBM 102 2 0 14 May 2018
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization Peter L. Bartlett S. Evans Philip M. Long 228 32 0 13 Apr 2018
A Compact Network Learning Model for Distribution Regression C. Kou H. Lee Teck Khim Ng 127 10 0 13 Apr 2018
MGGAN: Solving Mode Collapse using Manifold Guided Training Duhyeon Bang Hyunjung Shim GAN 127 89 0 12 Apr 2018
Latent Space Policies for Hierarchical Reinforcement Learning Tuomas Haarnoja Kristian Hartikainen Pieter Abbeel Sergey Levine BDL 173 200 0 09 Apr 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 390 479 0 03 Apr 2018
Sylvester Normalizing Flows for Variational InferenceConference on Uncertainty in Artificial Intelligence (UAI), 2018 Rianne van den Berg Leonard Hasenclever Jakub M. Tomczak Max Welling BDL DRL 340 257 0 15 Mar 2018
Learning the Base Distribution in Implicit Generative Models Cem Subakan Oluwasanmi Koyejo Paris Smaragdis GAN DRL 99 8 0 12 Mar 2018
Is Generator Conditioning Causally Related to GAN Performance? Augustus Odena Jacob Buckman Catherine Olsson Tom B. Brown C. Olah Colin Raffel Ian Goodfellow AI4CE 169 120 0 23 Feb 2018
BRUNO: A Deep Recurrent Model for Exchangeable Data I. Korshunova Jonas Degrave Ferenc Huszár Y. Gal Arthur Gretton J. Dambre BDL 148 35 0 21 Feb 2018
i-RevNet: Deep Invertible Networks J. Jacobsen A. Smeulders Edouard Oyallon 254 348 0 20 Feb 2018
Distribution Matching in Variational Inference Mihaela Rosca Balaji Lakshminarayanan S. Mohamed GAN CML DRL 343 101 0 19 Feb 2018
Leveraging the Exact Likelihood of Deep Latent Variable Models Pierre-Alexandre Mattei J. Frellsen DRL 250 68 0 13 Feb 2018
Neural Network Renormalization Group Shuo-Hui Li Lei Wang BDL DRL 215 136 0 08 Feb 2018
Transformation Autoregressive Networks Junier B. Oliva Kumar Avinava Dubey Manzil Zaheer Barnabás Póczós Ruslan Salakhutdinov Eric Xing J. Schneider OOD 284 88 0 30 Jan 2018
Improved Training of Generative Adversarial Networks Using Representative Features Duhyeon Bang Hyunjung Shim GAN 185 38 0 28 Jan 2018
Inference Suboptimality in Variational Autoencoders Chris Cremer Xuechen Li David Duvenaud DRL BDL 301 294 0 10 Jan 2018
PixelSNAIL: An Improved Autoregressive Generative ModelInternational Conference on Machine Learning (ICML), 2017 Xi Chen Nikhil Mishra Mostafa Rohaninejad Pieter Abbeel DRL DiffM BDL GAN 212 297 0 28 Dec 2017
Integral Equations and Machine Learning A. Keller Ken Dahm 109 13 0 17 Dec 2017
How well does your sampler really work? Ryan D. Turner Brady Neal 126 4 0 16 Dec 2017
Toward Multimodal Image-to-Image Translation Jun-Yan Zhu Richard Y. Zhang Deepak Pathak Trevor Darrell Alexei A. Efros Oliver Wang Eli Shechtman 366 1,412 0 30 Nov 2017
Auxiliary Guided Autoregressive Variational Autoencoders Thomas Lucas Jakob Verbeek GAN DRL 124 21 0 30 Nov 2017
Parallel WaveNet: Fast High-Fidelity Speech Synthesis Aaron van den Oord Yazhe Li Igor Babuschkin Karen Simonyan Oriol Vinyals ... Alex Graves Helen King T. Walters Dan Belov Demis Hassabis 384 890 0 28 Nov 2017
Generalizing Hamiltonian Monte Carlo with Neural Networks Daniel Levy Matthew D. Hoffman Jascha Narain Sohl-Dickstein BDL 248 131 0 25 Nov 2017
An Iterative Closest Points Approach to Neural Generative Models Joose Rajamäki Perttu Hämäläinen 3DPC 179 1 0 16 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 548 770 0 15 Nov 2017
Convolutional Normalizing Flows Guoqing Zheng Yiming Yang J. Carbonell BDL 136 11 0 07 Nov 2017