NVAE: A Deep Hierarchical Variational Autoencoder

8 July 2020

Papers citing "NVAE: A Deep Hierarchical Variational Autoencoder"

50 / 225 papers shown

Title
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 152 14,738 0 20 Dec 2021
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs Zhisheng Xiao Karsten Kreis Arash Vahdat DiffM 42 541 0 15 Dec 2021
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion Tim Dockhorn Arash Vahdat Karsten Kreis DiffM 30 231 0 14 Dec 2021
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias Frederic Koehler Viraj Mehta Chenghui Zhou Andrej Risteski DRL 41 12 0 13 Dec 2021
Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation Minghui Hu Yujie Wang Tat-Jen Cham Jianfei Yang P.N.Suganthan DiffM 18 41 0 03 Dec 2021
$$\ell_\infty$-Robustness and Beyond: Unleashing Efficient Adversarial Training$ $\ell_\infty$ -Robustness and Beyond: Unleashing Efficient Adversarial Training H. M. Dolatabadi S. Erfani C. Leckie OOD AAML 24 11 0 01 Dec 2021
Forward Operator Estimation in Generative Models with Kernel Transfer Operators Z. Huang Rudrasis Chakraborty Vikas Singh GAN 16 3 0 01 Dec 2021
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation Konpat Preechakul Nattanat Chatthee Suttisak Wizadwongsa Supasorn Suwajanakorn SyDa DiffM 58 417 0 30 Nov 2021
Exploring Versatile Prior for Human Motion via Motion Frequency Guidance Jiachen Xu Min Wang Jing-yu Gong Wentao Liu Chao Qian Yuan Xie Lizhuang Ma 35 9 0 25 Nov 2021
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes Sam Bond-Taylor P. Hessey Hiroshi Sasaki T. Breckon Chris G. Willcocks DiffM 27 71 0 24 Nov 2021
Lossless Compression with Probabilistic Circuits Guy Van den Broeck Stephan Mandt Mathias Niepert TPM 21 21 0 23 Nov 2021
Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction Xili Dai Shengbang Tong Mingyang Li Ziyang Wu Michael Psenka ... Pengyuan Zhai Yaodong Yu Xiaojun Yuan Harry Shum Yi Ma 25 30 0 12 Nov 2021
Palette: Image-to-Image Diffusion Models Chitwan Saharia William Chan Huiwen Chang Chris A. Lee Jonathan Ho Tim Salimans David J. Fleet Mohammad Norouzi DiffM VLM 366 1,597 0 10 Nov 2021
Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder Yi Huang Yihui Ren Shinjae Yoo Jin-zhi Huang 17 10 0 09 Nov 2021
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory T. Chen Guan-Horng Liu Evangelos A. Theodorou DiffM OT 174 165 0 21 Oct 2021
Variational Predictive Routing with Nested Subjective Timescales Alexey Zakharov Qinghai Guo Z. Fountas BDL AI4TS 43 9 0 21 Oct 2021
Controllable and Compositional Generation with Latent-Space Energy-Based Models Weili Nie Arash Vahdat Anima Anandkumar 22 78 0 21 Oct 2021
Unsupervised Object Learning via Common Fate Matthias Tangemann Steffen Schneider Julius von Kügelgen Francesco Locatello Peter V. Gehler Thomas Brox Matthias Kümmerer Matthias Bethge Bernhard Schölkopf OCL 36 23 0 13 Oct 2021
Vector-quantized Image Modeling with Improved VQGAN Jiahui Yu Xin Li Jing Yu Koh Han Zhang Ruoming Pang James Qin Alexander Ku Yuanzhong Xu Jason Baldridge Yonghui Wu ViT VLM DRL 49 485 0 09 Oct 2021
Generative Modeling with Optimal Transport Maps Litu Rout Alexander Korotin Evgeny Burnaev OT DiffM 122 65 0 06 Oct 2021
A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction Moitreya Chatterjee Narendra Ahuja A. Cherian UQCV VGen BDL 44 17 0 06 Oct 2021
Autoregressive Diffusion Models Emiel Hoogeboom Alexey A. Gritsenko Jasmijn Bastings Ben Poole Rianne van den Berg Tim Salimans DiffM 45 145 0 05 Oct 2021
A moment-matching metric for latent variable generative models Cédric Beaulac 19 1 0 04 Oct 2021
Fully Spiking Variational Autoencoder Hiromichi Kamata Yusuke Mukuta Tatsuya Harada BDL DRL 43 41 0 26 Sep 2021
Entropic Issues in Likelihood-Based OOD Detection Anthony L. Caterini G. Loaiza-Ganem OODD 24 15 0 22 Sep 2021
Recommender systems based on graph embedding techniques: A comprehensive review Yue Deng 44 22 0 20 Sep 2021
TrAISformer -- A Transformer Network with Sparse Augmented Data Representation and Cross Entropy Loss for AIS-based Vessel Trajectory Prediction Duong Nguyen Ronan Fablet 21 24 0 08 Sep 2021
An Introduction to Variational Inference Ankush Ganguly Samuel W. F. Earp BDL 22 20 0 30 Aug 2021
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis Patrick Esser Robin Rombach A. Blattmann Bjorn Ommer DiffM 38 157 0 19 Aug 2021
LSD-StructureNet: Modeling Levels of Structural Detail in 3D Part Hierarchies Dominic Roberts Aram Danielyan Hang Chu Mani Golparvar-Fard David A. Forsyth 3DPC 3DV 43 8 0 18 Aug 2021
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models Jooyoung Choi Sungwon Kim Yonghyun Jeong Youngjune Gwon Sungroh Yoon DiffM 54 697 0 06 Aug 2021
Pragmatic Image Compression for Human-in-the-Loop Decision-Making S. Reddy Anca Dragan Sergey Levine OffRL 44 13 0 07 Jul 2021
Variational Diffusion Models Diederik P. Kingma Tim Salimans Ben Poole Jonathan Ho DiffM 94 1,069 0 01 Jul 2021
Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb Stefan Bauer M. Besserve Bernhard Schölkopf DRL 49 17 0 30 Jun 2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network Zhibin Duan Dongsheng Wang Bo Chen Chaojie Wang Wenchao Chen Yewen Li Jie Ren Mingyuan Zhou BDL 37 39 0 30 Jun 2021
On Incorporating Inductive Biases into VAEs Ning Miao Emile Mathieu N. Siddharth Yee Whye Teh Tom Rainforth CML DRL 30 10 0 25 Jun 2021
Symmetric Wasserstein Autoencoders S. Sun Hong Guo DiffM GAN 26 0 0 24 Jun 2021
Non Gaussian Denoising Diffusion Models Eliya Nachmani Robin San Roman Lior Wolf VLM DiffM 35 48 0 14 Jun 2021
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation Abhishek Sinha Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 30 118 0 12 Jun 2021
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior Sang-gil Lee Heeseung Kim Chaehun Shin Xu Tan Chang-Shu Liu Qi Meng Tao Qin Wei Chen Sung-Hoon Yoon Tie-Yan Liu DiffM 29 81 0 11 Jun 2021
Score-based Generative Modeling in Latent Space Arash Vahdat Karsten Kreis Jan Kautz DiffM 16 659 0 10 Jun 2021
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation Dongjun Kim Seung-Jae Shin Kyungwoo Song Wanmo Kang Il-Chul Moon 34 91 0 10 Jun 2021
On Memorization in Probabilistic Deep Generative Models G. V. D. Burg Christopher K. I. Williams TDI 25 59 0 06 Jun 2021
Driving-Signal Aware Full-Body Avatars Timur M. Bagautdinov Chenglei Wu Tomas Simon F. Prada Takaaki Shiratori S. Wei Weipeng Xu Yaser Sheikh Jason M. Saragih 3DH 21 80 0 21 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 35 124 0 14 May 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 85 7,480 0 11 May 2021
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement Martin Engelcke Oiwi Parker Jones Ingmar Posner OCL 37 115 0 20 Apr 2021
Few-shot Image Generation via Cross-domain Correspondence Utkarsh Ojha Yijun Li Jingwan Lu Alexei A. Efros Yong Jae Lee Eli Shechtman Richard Y. Zhang 25 259 0 13 Apr 2021
NeRF-VAE: A Geometry Aware 3D Scene Generative Model Adam R. Kosiorek Heiko Strathmann Daniel Zoran Pol Moreno R. Schneider Sovna Mokrá Danilo Jimenez Rezende DRL 37 139 0 01 Apr 2021
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling DJordje Miladinović Aleksandar Stanić Stefan Bauer Jürgen Schmidhuber J. M. Buhmann DRL 23 9 0 16 Mar 2021