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Sylvester Normalizing Flows for Variational Inference

15 March 2018

Papers citing "Sylvester Normalizing Flows for Variational Inference"

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Title
Generalization of the Change of Variables Formula with Applications to Residual Flows Niklas Koenen Marvin N. Wright Peter Maass Jens Behrmann 43 2 0 09 Jul 2021
Viscos Flows: Variational Schur Conditional Sampling With Normalizing Flows Vincent Moens Aivar Sootla H. Ammar Jun Wang TPM 65 1 0 06 Jul 2021
On the Generative Utility of Cyclic Conditionals Chang-Shu Liu Haoyue Tang Tao Qin Jintao Wang Tie-Yan Liu 82 3 0 30 Jun 2021
On Incorporating Inductive Biases into VAEs Ning Miao Emile Mathieu N. Siddharth Yee Whye Teh Tom Rainforth CML DRL 99 11 0 25 Jun 2021
Sparse Flows: Pruning Continuous-depth Models Lucas Liebenwein Ramin Hasani Alexander Amini Daniela Rus 116 17 0 24 Jun 2021
Distilling the Knowledge from Conditional Normalizing Flows Dmitry Baranchuk Vladimir Aliev Artem Babenko BDL 85 2 0 24 Jun 2021
Model Selection for Bayesian Autoencoders Ba-Hien Tran Simone Rossi Dimitrios Milios Pietro Michiardi Edwin V. Bonilla Maurizio Filippone BDL 82 13 0 11 Jun 2021
The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider T. Aarrestad M. Beekveld M. Bona A. Boveia S. Caron ... M. White E. Wulff E. Wallin K. Wozniak Z. Zhang 95 83 0 28 May 2021
Augmented KRnet for density estimation and approximation Xiaoliang Wan Keju Tang 69 5 0 26 May 2021
Universal Approximation of Residual Flows in Maximum Mean Discrepancy Zhifeng Kong Kamalika Chaudhuri UQCV 42 6 0 10 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 176 509 0 08 Mar 2021
Structured Dropout Variational Inference for Bayesian Neural Networks S. Nguyen Duong Nguyen Khai Nguyen Khoat Than Hung Bui Nhat Ho BDL DRL 70 8 0 16 Feb 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 47 8 0 12 Feb 2021
Invertible DenseNets with Concatenated LipSwish Yura Perugachi-Diaz Jakub M. Tomczak Sandjai Bhulai 133 20 0 04 Feb 2021
Cauchy-Schwarz Regularized Autoencoder Linh-Tam Tran Maja Pantic M. Deisenroth DRL BDL 75 17 0 06 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 216 98 0 10 Dec 2020
Accelerating Continuous Normalizing Flow with Trajectory Polynomial Regularization Han Huang Mi-Yen Yeh 69 8 0 08 Dec 2020
General Invertible Transformations for Flow-based Generative Modeling Jakub M. Tomczak DRL AI4CE 43 4 0 30 Nov 2020
Prior Flow Variational Autoencoder: A density estimation model for Non-Intrusive Load Monitoring Luis Felipe M.O. Henriques Eduardo Morgan S. Colcher Ruy Luiz Milidiú 18 0 0 30 Nov 2020
Predictive Coding, Variational Autoencoders, and Biological Connections Joseph Marino DRL AI4CE 95 45 0 15 Nov 2020
Training Invertible Linear Layers through Rank-One Perturbations Andreas Krämer Jonas Köhler Frank Noé 49 0 0 14 Oct 2020
Self-Supervised Variational Auto-Encoders Ioannis Gatopoulos Jakub M. Tomczak 53 13 0 05 Oct 2020
One Reflection Suffice Alexander Mathiasen Frederik Hvilshoj 31 0 0 30 Sep 2020
What if Neural Networks had SVDs? Alexander Mathiasen Frederik Hvilshoj Jakob Rødsgaard Jørgensen Anshul Nasery Davide Mottin 51 10 0 29 Sep 2020
Quasi-Autoregressive Residual (QuAR) Flows Achintya Gopal TPM 29 2 0 16 Sep 2020
Learning more expressive joint distributions in multimodal variational methods S. Nedelkoski Mihail Bogojeski O. Kao 28 1 0 08 Sep 2020
Reconstruction Bottlenecks in Object-Centric Generative Models Martin Engelcke Oiwi Parker Jones Ingmar Posner OCL 94 24 0 13 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 82 92 0 06 Jul 2020
VAE-KRnet and its applications to variational Bayes Xiaoliang Wan Shuangqing Wei BDL DRL 89 13 0 29 Jun 2020
Reliable Categorical Variational Inference with Mixture of Discrete Normalizing Flows Tomasz Kuśmierczyk Arto Klami BDL DRL 29 0 0 28 Jun 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 74 22 0 26 Jun 2020
Categorical Normalizing Flows via Continuous Transformations Phillip Lippe E. Gavves BDL 136 44 0 17 Jun 2020
Learning normalizing flows from Entropy-Kantorovich potentials Chris Finlay Augusto Gerolin Adam M. Oberman Aram-Alexandre Pooladian 102 24 0 10 Jun 2020
Super-resolution Variational Auto-Encoders Ioannis Gatopoulos M. Stol Jakub M. Tomczak SupR DiffM 51 15 0 09 Jun 2020
Graphical Normalizing Flows Antoine Wehenkel Gilles Louppe TPM BDL 72 39 0 03 Jun 2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities Jonas Köhler Leon Klein Frank Noé DRL 143 279 0 03 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 83 29 0 02 Jun 2020
The Expressive Power of a Class of Normalizing Flow Models Zhifeng Kong Kamalika Chaudhuri TPM 82 53 0 31 May 2020
Variational Neural Machine Translation with Normalizing Flows Hendra Setiawan Matthias Sperber Udhay Nallasamy Matthias Paulik DRL 58 12 0 28 May 2020
Invertible Image Rescaling Mingqing Xiao Shuxin Zheng Chang-Shu Liu Yaolong Wang Di He Guolin Ke Jiang Bian Zhouchen Lin Tie-Yan Liu SupR 95 241 0 12 May 2020
Time Dependence in Non-Autonomous Neural ODEs Jared Davis K. Choromanski Jacob Varley Honglak Lee Jean-Jacques E. Slotine Valerii Likhosterov Adrian Weller A. Makadia Vikas Sindhwani OOD AI4TS 40 15 0 05 May 2020
Roundtrip: A Deep Generative Neural Density Estimator Qiao Liu Jiaze Xu R. Jiang W. Wong OT 44 4 0 20 Apr 2020
Decoupling Global and Local Representations via Invertible Generative Flows Xuezhe Ma X. Kong Shanghang Zhang Eduard H. Hovy DRL 84 3 0 12 Apr 2020
Scaling Bayesian inference of mixed multinomial logit models to very large datasets Filipe Rodrigues BDL 100 3 0 11 Apr 2020
TraDE: Transformers for Density Estimation Rasool Fakoor Pratik Chaudhari Jonas W. Mueller Alex Smola 86 30 0 06 Apr 2020
Stochastic Flows and Geometric Optimization on the Orthogonal Group K. Choromanski David Cheikhi Jared Davis Valerii Likhosherstov Achille Nazaret ... Yuan Gao Aldo Pacchiano Tamás Sarlós Adrian Weller Vikas Sindhwani AI4CE 35 7 0 30 Mar 2020
Woodbury Transformations for Deep Generative Flows You Lu Bert Huang 85 16 0 27 Feb 2020
Gradient Boosted Normalizing Flows Robert Giaquinto A. Banerjee BDL DRL 18 1 0 27 Feb 2020
Max-Affine Spline Insights into Deep Generative Networks Randall Balestriero Sébastien Paris Richard Baraniuk DRL AI4CE 47 15 0 26 Feb 2020
Amortised Learning by Wake-Sleep W. Li Theodore H. Moskovitz Heishiro Kanagawa M. Sahani OOD 104 7 0 22 Feb 2020