Improving Variational Inference with Inverse Autoregressive Flow

15 June 2016

Papers citing "Improving Variational Inference with Inverse Autoregressive Flow"

50 / 308 papers shown

Title
Trumpets: Injective Flows for Inference and Inverse Problems K. Kothari AmirEhsan Khorashadizadeh Maarten V. de Hoop Ivan Dokmanić TPM 22 50 0 20 Feb 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 11 7 0 12 Feb 2021
Neural representation and generation for RNA secondary structures Zichao Yan William L. Hamilton Mathieu Blanchette 32 2 0 01 Feb 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 15 241 0 09 Jan 2021
Variational Determinant Estimation with Spherical Normalizing Flows Simon Passenheim Emiel Hoogeboom BDL 21 1 0 24 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 112 95 0 10 Dec 2020
Regularization with Latent Space Virtual Adversarial Training Genki Osada Budrul Ahsan Revoti Prasad Bora Takashi Nishide 24 14 0 26 Nov 2020
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images R. Child BDL VLM 31 336 0 20 Nov 2020
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks Thomas Bird F. Kingma David Barber SyDa MQ AI4CE 18 9 0 26 Oct 2020
Variational Bayesian Unlearning Q. Nguyen Bryan Kian Hsiang Low Patrick Jaillet BDL MU 17 121 0 24 Oct 2020
A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing Chunchuan Lyu Shay B. Cohen Ivan Titov 24 11 0 23 Oct 2020
Principled Interpolation in Normalizing Flows Samuel G. Fadel Sebastian Mair Ricardo da S. Torres Ulf Brefeld 75 3 0 22 Oct 2020
Hierarchical Autoregressive Modeling for Neural Video Compression Ruihan Yang Yibo Yang Joseph Marino Stephan Mandt BDL VGen 104 46 0 19 Oct 2020
Dirichlet Graph Variational Autoencoder Jia Li Tomas Yu Jiajin Li Honglei Zhang Kangfei Zhao Yu Rong Hong Cheng Junzhou Huang BDL 11 52 0 09 Oct 2020
Improving Sequential Latent Variable Models with Autoregressive Flows Joseph Marino Lei Chen Jiawei He Stephan Mandt BDL AI4TS 21 12 0 07 Oct 2020
Variational Disentanglement for Rare Event Modeling Zidi Xiu Chenyang Tao M. Gao Connor Davis B. Goldstein Ricardo Henao CML DRL 24 6 0 17 Sep 2020
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha Matthew O'Kelly Russ Tedrake John C. Duchi 39 47 0 24 Aug 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks Yaniv Yacoby Weiwei Pan Finale Doshi-Velez CML DRL 27 25 0 14 Jul 2020
AUTO3D: Novel view synthesis through unsupervisely learned variational viewpoint and global 3D representation Xiaofeng Liu Tong Che Yiqun Lu Chao Yang Site Li J. You 3DV 41 21 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 T. Toda 11 18 0 11 Jul 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 19 19 0 10 Jul 2020
Learning Sparse Prototypes for Text Generation Junxian He Taylor Berg-Kirkpatrick Graham Neubig 19 23 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 10 22 0 26 Jun 2020
Learning Physical Graph Representations from Visual Scenes Daniel M. Bear Chaofei Fan Damian Mrowca Yunzhu Li S. Alter ... Jeremy Schwartz Li Fei-Fei Jiajun Wu J. Tenenbaum Daniel L. K. Yamins SSL GNN SSeg AI4CE 39 79 0 22 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 116 16,915 0 19 Jun 2020
Categorical Normalizing Flows via Continuous Transformations Phillip Lippe E. Gavves BDL 13 43 0 17 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Jackson Wang Roger C. Grosse J. Jacobsen 16 92 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 17 169 0 16 Jun 2020
A Variational Approach to Privacy and Fairness Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund FaML DRL 14 25 0 11 Jun 2020
Learning normalizing flows from Entropy-Kantorovich potentials Chris Finlay Augusto Gerolin Adam M. Oberman Aram-Alexandre Pooladian 20 23 0 10 Jun 2020
Deep generative models for musical audio synthesis M. Huzaifah L. Wyse 19 20 0 10 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 16 32 0 09 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 17 28 0 02 Jun 2020
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression Domagoj Cevid Loris Michel Jeffrey Näf N. Meinshausen Peter Buhlmann 30 39 0 29 May 2020
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models Zhijian Ou Yunfu Song BDL 26 8 0 28 May 2020
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis Rafael Valle Kevin J. Shih R. Prenger Bryan Catanzaro 8 119 0 12 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 17 234 0 12 May 2020
Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders Saeid Asgari Taghanaki Mohammad Havaei Alex Lamb Aditya Sanghi Aram Danielyan Tonya Custis DRL 25 7 0 12 May 2020
Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speech Geng Yang Shan Yang Kai-Chun Liu Peng Fang Wei-Neng Chen Lei Xie 42 198 0 11 May 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away Qile Zhu Jianlin Su Wei Bi Xiaojiang Liu Xiyao Ma Xiaolin Li D. Wu BDL DRL 29 61 0 27 Apr 2020
PatchVAE: Learning Local Latent Codes for Recognition Kamal Gupta Saurabh Singh Abhinav Shrivastava SSL DRL 14 20 0 07 Apr 2020
Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space Chunyuan Li Xiang Gao Yuan Li Baolin Peng Xiujun Li Yizhe Zhang Jianfeng Gao SSL DRL 30 181 0 05 Apr 2020
Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model Calibration Vojtech Kejzlar T. Maiti 6 6 0 28 Mar 2020
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis Aman Sinha Matthew O'Kelly Hongrui Zheng Rahul Mangharam John C. Duchi Russ Tedrake OffRL 66 26 0 09 Mar 2020
The Variational InfoMax Learning Objective Vincenzo Crescimanna Bruce P. Graham 11 0 0 07 Mar 2020
Diverse and Admissible Trajectory Forecasting through Multimodal Context Understanding Seonguk Park Gyubok Lee Manoj Bhat Jimin Seo Minseok Kang Jonathan M Francis Ashwin R. Jadhav Paul Pu Liang Louis-Philippe Morency 136 119 0 06 Mar 2020
Gravitational-wave parameter estimation with autoregressive neural network flows Stephen R. Green C. Simpson J. Gair BDL 83 87 0 18 Feb 2020
Balancing reconstruction error and Kullback-Leibler divergence in Variational Autoencoders Andrea Asperti Matteo Trentin DRL 22 94 0 18 Feb 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 24 87 0 17 Feb 2020
Variational Autoencoders with Riemannian Brownian Motion Priors Dimitris Kalatzis David Eklund Georgios Arvanitidis Søren Hauberg BDL DRL 58 48 0 12 Feb 2020