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Analyzing Inverse Problems with Invertible Neural Networks

14 August 2018

Lena Maier-Hein

Papers citing "Analyzing Inverse Problems with Invertible Neural Networks"

44 / 44 papers shown

Title
Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning Sanghwan Bae Jiwoo Hong Min Young Lee Hanbyul Kim Jeongyeon Nam Donghyun Kwak OffRL LRM 107 0 0 04 Apr 2025
A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations Naveen Gupta Medha Sawhney Arka Daw Youzuo Lin Anuj Karpatne MedIm AI4CE 94 3 0 15 Oct 2024
Amortized Bayesian Multilevel Models Daniel Habermann Marvin Schmitt Lars Kühmichel Andreas Bulling Stefan T. Radev Paul-Christian Bürkner 206 4 0 23 Aug 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 88 2 0 29 Jul 2024
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Jayneel Parekh Quentin Bouniot Pavlo Mozharovskyi A. Newson Florence dÁlché-Buc SSL 129 1 0 01 Jul 2024
Stability of Data-Dependent Ridge-Regularization for Inverse Problems Sebastian Neumayer Fabian Altekrüger 75 1 0 18 Jun 2024
Variational Bayesian Optimal Experimental Design with Normalizing Flows Jiayuan Dong Christian L. Jacobsen Mehdi Khalloufi Maryam Akram Wanjiao Liu Karthik Duraisamy Xun Huan BDL 152 8 0 08 Apr 2024
Application-driven Validation of Posteriors in Inverse Problems T. Adler Jan-Hinrich Nolke Annika Reinke M. Tizabi Sebastian Gruber ... Lynton Ardizzone Paul F. Jaeger Florian Buettner Ullrich Kothe Lena Maier-Hein MedIm 66 1 0 18 Sep 2023
Embodied Self-Supervised Learning (EMSSL) with Sampling and Training Coordination for Robot Arm Inverse Kinematics Model Learning Weiming Qu Tianlin Liu Xihong Wu D. Luo 64 2 0 26 Feb 2023
Generative Graphical Inverse Kinematics Oliver Limoyo Filip Marić Matthew Giamou Petra Alexson Ivan Petrović Jonathan Kelly 93 1 0 19 Sep 2022
$Variational inference of fractional Brownian motion with linear computational complexity$ Variational inference of fractional Brownian motion with linear computational complexity Hippolyte Verdier Franccois Laurent Alhassan Cassé Christian L. Vestergaard Jean-Baptiste Masson 165 6 0 15 Mar 2022
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 295 3,134 0 09 Jul 2018
Training Generative Reversible Networks R. Schirrmeister Patryk Chrabkaszcz Frank Hutter T. Ball BDL GAN 23 8 0 05 Jun 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 151 442 0 03 Apr 2018
Sylvester Normalizing Flows for Variational Inference Rianne van den Berg Leonard Hasenclever Jakub M. Tomczak Max Welling BDL DRL 92 253 0 15 Mar 2018
i-RevNet: Deep Invertible Networks J. Jacobsen A. Smeulders Edouard Oyallon 83 333 0 20 Feb 2018
Conditional Density Estimation with Bayesian Normalising Flows Brian L. Trippe Richard Turner BDL 78 84 0 14 Feb 2018
Invertible Autoencoder for domain adaptation Yunfei Teng A. Choromańska Mariusz Bojarski 59 23 0 10 Feb 2018
Toward Multimodal Image-to-Image Translation Jun-Yan Zhu Richard Y. Zhang Deepak Pathak Trevor Darrell Alexei A. Efros Oliver Wang Eli Shechtman 123 1,352 0 30 Nov 2017
Wasserstein Auto-Encoders Ilya O. Tolstikhin Olivier Bousquet Sylvain Gelly B. Schölkopf DRL 122 1,057 0 05 Nov 2017
The Reversible Residual Network: Backpropagation Without Storing Activations Aidan Gomez Mengye Ren R. Urtasun Roger C. Grosse 74 550 0 14 Jul 2017
Learning Disentangled Representations with Semi-Supervised Deep Generative Models Siddharth Narayanaswamy Brooks Paige Jan-Willem van de Meent Alban Desmaison Noah D. Goodman Pushmeet Kohli Frank Wood Philip Torr DRL CoGe 124 362 0 01 Jun 2017
Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models Aditya Grover Manik Dhar Stefano Ermon GAN 73 24 0 24 May 2017
Semantically Decomposing the Latent Spaces of Generative Adversarial Networks Chris Donahue Zachary Chase Lipton Akshay Balsubramani Julian McAuley GAN 70 120 0 22 May 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 210 1,354 0 19 May 2017
Comparison of Maximum Likelihood and GAN-based training of Real NVPs Ivo Danihelka Balaji Lakshminarayanan Benigno Uria Daan Wierstra Peter Dayan GAN 55 53 0 15 May 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 359 4,709 0 15 Mar 2017
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications Tim Salimans A. Karpathy Xi Chen Diederik P. Kingma 105 942 0 19 Jan 2017
Improving Variational Auto-Encoders using Householder Flow Jakub M. Tomczak Max Welling BDL DRL 76 175 0 29 Nov 2016
Image-to-Image Translation with Conditional Adversarial Networks Phillip Isola Jun-Yan Zhu Tinghui Zhou Alexei A. Efros SSeg 326 19,651 0 21 Nov 2016
Conditional Image Generation with PixelCNN Decoders Aaron van den Oord Nal Kalchbrenner Oriol Vinyals L. Espeholt Alex Graves Koray Kavukcuoglu VLM 209 2,513 0 16 Jun 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 142 1,820 0 15 Jun 2016
Adversarially Learned Inference Vincent Dumoulin Ishmael Belghazi Ben Poole Olivier Mastropietro Alex Lamb Martín Arjovsky Aaron Courville GAN 79 1,314 0 02 Jun 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 272 3,702 0 26 May 2016
Neural Autoregressive Distribution Estimation Benigno Uria Marc-Alexandre Côté Karol Gregor Iain Murray Hugo Larochelle 81 314 0 07 May 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 285 4,793 0 04 Jan 2016
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 226 1,514 0 08 Jun 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 261 751 0 06 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 318 4,182 0 21 May 2015
MADE: Masked Autoencoder for Distribution Estimation M. Germain Karol Gregor Iain Murray Hugo Larochelle OOD SyDa UQCV 172 868 0 12 Feb 2015
Conditional Generative Adversarial Nets M. Berk Mirza Simon Osindero GAN SyDa AI4CE 258 10,409 0 06 Nov 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 126 2,261 0 30 Oct 2014
High-Dimensional Probability Estimation with Deep Density Models Oren Rippel Ryan P. Adams 176 124 0 20 Feb 2013
Approximate Bayesian computation (ABC) gives exact results under the assumption of model error Richard D. Wilkinson 108 274 0 20 Nov 2008