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
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation Chris Waites Rachel Cummings 19 15 0 25 Mar 2021
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL Clément Romac Rémy Portelas Katja Hofmann Pierre-Yves Oudeyer 27 21 0 17 Mar 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments Lizhen Nie Mao Ye Qiang Liu D. Nicolae CML 22 68 0 14 Mar 2021
An Introduction to Deep Generative Modeling Lars Ruthotto E. Haber AI4CE 33 220 0 09 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 41 481 0 08 Mar 2021
EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss Zhisheng Xiao Qing Yan Y. Amit 32 2 0 23 Feb 2021
Trumpets: Injective Flows for Inference and Inverse Problems K. Kothari AmirEhsan Khorashadizadeh Maarten V. de Hoop Ivan Dokmanić TPM 24 50 0 20 Feb 2021
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 23 23 0 19 Feb 2021
Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows Anubhab Ghosh Antoine Honoré Dong Liu G. Henter S. Chatterjee BDL VLM 35 7 0 15 Feb 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li David Duvenaud BDL UQCV 27 46 0 12 Feb 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 19 7 0 12 Feb 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 34 33 0 12 Feb 2021
MALI: A memory efficient and reverse accurate integrator for Neural ODEs Juntang Zhuang Nicha Dvornek S. Tatikonda James S. Duncan 24 49 0 09 Feb 2021
Invertible Neural Networks versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence A. Andrle N. Farchmin Paul Hagemann Sebastian Heidenreich V. Soltwisch Gabriele Steidl 69 16 0 05 Feb 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation Youzhi Luo Keqiang Yan Shuiwang Ji DRL 185 187 0 01 Feb 2021
Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting Nam H. Nguyen Brian Quanz BDL AI4TS 137 66 0 25 Jan 2021
Adversarial Text-to-Image Synthesis: A Review Stanislav Frolov Tobias Hinz Federico Raue Jörn Hees Andreas Dengel EGVM 22 175 0 25 Jan 2021
Maximum Likelihood Training of Score-Based Diffusion Models Yang Song Conor Durkan Iain Murray Stefano Ermon DiffM 64 625 0 22 Jan 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 24 241 0 09 Jan 2021
Variational Determinant Estimation with Spherical Normalizing Flows Simon Passenheim Emiel Hoogeboom BDL 31 1 0 24 Dec 2020
Flow-based Generative Models for Learning Manifold to Manifold Mappings Xingjian Zhen Rudrasis Chakraborty Liu Yang Vikas Singh DRL MedIm 31 9 0 18 Dec 2020
Motion Mappings for Continuous Bilateral Teleoperation Xiao Gao João Silvério Emmanuel Pignat Sylvain Calinon Miao Li Xiaohui Xiao 8 21 0 11 Dec 2020
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 119 95 0 10 Dec 2020
Bayesian Image Reconstruction using Deep Generative Models Razvan Marinescu Daniel Moyer Polina Golland OOD DiffM 23 39 0 08 Dec 2020
The Hidden Uncertainty in a Neural Networks Activations Janis Postels Hermann Blum Yannick Strümpler Cesar Cadena Roland Siegwart Luc Van Gool Federico Tombari UQCV 30 22 0 05 Dec 2020
Image Generators with Conditionally-Independent Pixel Synthesis Ivan Anokhin K. Demochkin Taras Khakhulin Gleb Sterkin Victor Lempitsky Denis Korzhenkov 36 156 0 27 Nov 2020
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 46 6,088 0 26 Nov 2020
Regularization with Latent Space Virtual Adversarial Training Genki Osada Budrul Ahsan Revoti Prasad Bora Takashi Nishide 30 14 0 26 Nov 2020
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images R. Child BDL VLM 56 336 0 20 Nov 2020
Self Normalizing Flows Thomas Anderson Keller Jorn W. T. Peters P. Jaini Emiel Hoogeboom Patrick Forré Max Welling 30 14 0 14 Nov 2020
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference M. Vandegar Michael Kagan Antoine Wehenkel Gilles Louppe 24 27 0 11 Nov 2020
Wave-Tacotron: Spectrogram-free end-to-end text-to-speech synthesis Ron J. Weiss RJ Skerry-Ryan Eric Battenberg Soroosh Mariooryad Diederik P. Kingma 21 97 0 06 Nov 2020
Can We Trust Deep Speech Prior? Ying Shi Haolin Chen Zhiyuan Tang Lantian Li Dong Wang Jiqing Han 27 1 0 04 Nov 2020
Transforming Gaussian Processes With Normalizing Flows Juan Maroñas Oliver Hamelijnck Jeremias Knoblauch Theodoros Damoulas 23 34 0 03 Nov 2020
Toward a Generalization Metric for Deep Generative Models Hoang Thanh-Tung T. Tran 35 5 0 02 Nov 2020
Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging He Sun Katherine Bouman UQCV 17 74 0 27 Oct 2020
Wavelet Flow: Fast Training of High Resolution Normalizing Flows Jason J. Yu Konstantinos G. Derpanis Marcus A. Brubaker TPM 32 41 0 26 Oct 2020
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks Thomas Bird F. Kingma David Barber SyDa MQ AI4CE 26 9 0 26 Oct 2020
Principled Interpolation in Normalizing Flows Samuel G. Fadel Sebastian Mair Ricardo da S. Torres Ulf Brefeld 83 3 0 22 Oct 2020
Hierarchical Autoregressive Modeling for Neural Video Compression Ruihan Yang Yibo Yang Joseph Marino Stephan Mandt BDL VGen 112 46 0 19 Oct 2020
Orbital MCMC Kirill Neklyudov Max Welling 26 7 0 15 Oct 2020
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 83 1,292 0 08 Oct 2020
Representing Point Clouds with Generative Conditional Invertible Flow Networks Michal Stypulkowski Kacper Kania M. Zamorski Maciej Ziȩba Tomasz Trzciñski J. Chorowski 3DPC 24 4 0 07 Oct 2020
A Neural Network MCMC sampler that maximizes Proposal Entropy Zengyi Li Yubei Chen Friedrich T. Sommer 25 14 0 07 Oct 2020
Improving Sequential Latent Variable Models with Autoregressive Flows Joseph Marino Lei Chen Jiawei He Stephan Mandt BDL AI4TS 30 12 0 07 Oct 2020
Denoising Diffusion Implicit Models Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 56 6,944 0 06 Oct 2020
Self-Supervised Variational Auto-Encoders Ioannis Gatopoulos Jakub M. Tomczak 32 13 0 05 Oct 2020
Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation Wenhao Ding Baiming Chen Bo-wen Li Kim Ji Eun Ding Zhao AAML 16 99 0 16 Sep 2020
Learning Bloch Simulations for MR Fingerprinting by Invertible Neural Networks F. Balsiger Alain Jungo Olivier Scheidegger B. Marty M. Reyes 21 3 0 10 Aug 2020
Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications Xuan Li Xun Huang Jiahui Yu Ting-Chun Wang Arun Mallya GAN 28 153 0 06 Aug 2020