Glow: Generative Flow with Invertible 1x1 Convolutions

9 July 2018

Diederik P. Kingma

Papers citing "Glow: Generative Flow with Invertible 1x1 Convolutions"

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Title
Generative Flows with Matrix Exponential Chang Xiao Ligang Liu DRL 14 7 0 19 Jul 2020
Hybrid Discriminative-Generative Training via Contrastive Learning Hao Liu Pieter Abbeel SSL 23 40 0 17 Jul 2020
SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design Ari Seff Yaniv Ovadia Wenda Zhou Ryan P. Adams AI4CE 3DV 29 68 0 16 Jul 2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation Xuming Ran Mingkun Xu Lingrui Mei Qi Xu Quanying Liu OODD UQCV 42 51 0 16 Jul 2020
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows Ali Siahkoohi G. Rizzuti Philipp A. Witte Felix J. Herrmann AI4CE 19 16 0 15 Jul 2020
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows H. M. Dolatabadi S. Erfani C. Leckie AAML 19 66 0 15 Jul 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks Yaniv Yacoby Weiwei Pan Finale Doshi-Velez CML DRL 32 25 0 14 Jul 2020
Lessons Learned from the Training of GANs on Artificial Datasets Shichang Tang 22 18 0 13 Jul 2020
Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows Chris Cannella Mohammadreza Soltani Vahid Tarokh BDL 31 0 0 13 Jul 2020
Quasi-Periodic WaveNet: An Autoregressive Raw Waveform Generative Model with Pitch-dependent Dilated Convolution Neural Network Yi-Chiao Wu Tomoki Hayashi Patrick Lumban Tobing Kazuhiro Kobayashi Tomoki Toda 27 18 0 11 Jul 2020
EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision Siddharth Biswal Peiye Zhuang A. Pyrros Nasir Siddiqui Oluwasanmi Koyejo Jimeng Sun MedIm 27 5 0 10 Jul 2020
Self-Reflective Variational Autoencoder Ifigeneia Apostolopoulou Elan Rosenfeld A. Dubrawski OOD BDL DRL 27 0 0 10 Jul 2020
Invertible Zero-Shot Recognition Flows Yuming Shen Jie Qin Lei Huang BDL AI4CE 19 100 0 09 Jul 2020
NVAE: A Deep Hierarchical Variational Autoencoder Arash Vahdat Jan Kautz BDL 40 895 0 08 Jul 2020
Benefiting Deep Latent Variable Models via Learning the Prior and Removing Latent Regularization Rogan Morrow Wei-Chen Chiu DRL 26 0 0 07 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching Tianyu Pang Kun Xu Chongxuan Li Yang Song Stefano Ermon Jun Zhu DiffM 31 53 0 07 Jul 2020
Gradient Origin Networks Sam Bond-Taylor Chris G. Willcocks BDL DRL 15 18 0 06 Jul 2020
Black-box Adversarial Example Generation with Normalizing Flows H. M. Dolatabadi S. Erfani C. Leckie AAML 29 3 0 06 Jul 2020
Pseudo-Rehearsal for Continual Learning with Normalizing Flows Jary Pomponi Simone Scardapane A. Uncini 20 15 0 05 Jul 2020
Sliced Iterative Normalizing Flows B. Dai U. Seljak 16 36 0 01 Jul 2020
VAE-KRnet and its applications to variational Bayes Xiaoliang Wan Shuangqing Wei BDL DRL 24 13 0 29 Jun 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 19 22 0 26 Jun 2020
High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images Stephan J. Garbin Marek Kowalski Matthew W. Johnson Jamie Shotton 3DH 33 9 0 26 Jun 2020
SRFlow: Learning the Super-Resolution Space with Normalizing Flow Andreas Lugmayr Martin Danelljan Luc Van Gool Radu Timofte SupR DRL 23 356 0 25 Jun 2020
Normalizing Flows Across Dimensions Edmond Cunningham Renos Zabounidis Abhinav Agrawal Ina Fiterau Daniel Sheldon DRL 14 26 0 23 Jun 2020
Locally Masked Convolution for Autoregressive Models Ajay Jain Pieter Abbeel Deepak Pathak DiffM OffRL 39 31 0 22 Jun 2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression Rianne van den Berg A. Gritsenko Mostafa Dehghani C. Sønderby Tim Salimans 27 60 0 22 Jun 2020
Telescoping Density-Ratio Estimation Benjamin Rhodes Kai Xu Michael U. Gutmann 30 94 0 22 Jun 2020
Deep Residual Mixture Models Perttu Hämäläinen Martin Trapp Tuure Saloheimo Arno Solin 36 8 0 22 Jun 2020
Modeling Lost Information in Lossy Image Compression Yaolong Wang Mingqing Xiao Chang-Shu Liu Shuxin Zheng Tie-Yan Liu 32 23 0 22 Jun 2020
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators Takeshi Teshima Isao Ishikawa Koichi Tojo Kenta Oono Masahiro Ikeda Masashi Sugiyama 24 110 0 20 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 118 17,154 0 19 Jun 2020
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features R. Schirrmeister Yuxuan Zhou T. Ball Dan Zhang UQCV 22 88 0 18 Jun 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity S. Udrescu A. Tan Jiahai Feng Orisvaldo Neto Tailin Wu Max Tegmark 25 185 0 18 Jun 2020
STEER: Simple Temporal Regularization For Neural ODEs Arna Ghosh Harkirat Singh Behl Emilien Dupont Philip Torr Vinay P. Namboodiri BDL AI4TS 27 74 0 18 Jun 2020
Learning High-Resolution Domain-Specific Representations with a GAN Generator Danil Galeev Konstantin Sofiiuk D. Rukhovich Mikhail Romanov O. Barinova Anton Konushin GAN 39 15 0 18 Jun 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization Abhinav Agrawal Daniel Sheldon Justin Domke TPM BDL 19 38 0 18 Jun 2020
Neural Manifold Ordinary Differential Equations Aaron Lou Derek Lim Isay Katsman Leo Huang Qingxuan Jiang Ser-Nam Lim Christopher De Sa BDL AI4CE 23 79 0 18 Jun 2020
MoFlow: An Invertible Flow Model for Generating Molecular Graphs Chengxi Zang Fei Wang BDL 30 282 0 17 Jun 2020
Categorical Normalizing Flows via Continuous Transformations Phillip Lippe E. Gavves BDL 23 43 0 17 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Wang Roger C. Grosse J. Jacobsen 23 93 0 16 Jun 2020
Density of States Estimation for Out-of-Distribution Detection Warren Morningstar Cusuh Ham Andrew Gallagher Balaji Lakshminarayanan Alexander A. Alemi Joshua V. Dillon OODD 24 84 0 16 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 32 169 0 16 Jun 2020
Ordering Dimensions with Nested Dropout Normalizing Flows Artur Bekasov Iain Murray DRL 28 5 0 15 Jun 2020
Why Normalizing Flows Fail to Detect Out-of-Distribution Data Polina Kirichenko Pavel Izmailov A. Wilson OODD 22 271 0 15 Jun 2020
Improved Conditional Flow Models for Molecule to Image Synthesis Karren D. Yang Samuel Goldman Wengong Jin Alex X. Lu Regina Barzilay Tommi Jaakkola Caroline Uhler MedIm 16 7 0 15 Jun 2020
Globally Injective ReLU Networks Michael Puthawala K. Kothari Matti Lassas Ivan Dokmanić Maarten V. de Hoop 29 26 0 15 Jun 2020
Self-supervised Learning: Generative or Contrastive Xiao Liu Fanjin Zhang Zhenyu Hou Zhaoyu Wang Li Mian Jing Zhang Jie Tang SSL 54 1,588 0 15 Jun 2020
Exponential Tilting of Generative Models: Improving Sample Quality by Training and Sampling from Latent Energy Zhisheng Xiao Qing Yan Y. Amit DRL 8 8 0 15 Jun 2020
Enabling Counterfactual Survival Analysis with Balanced Representations Paidamoyo Chapfuwa Serge Assaad Shuxi Zeng Michael J. Pencina Lawrence Carin Ricardo Henao CML 16 2 0 14 Jun 2020