Resampled Priors for Variational Autoencoders

26 October 2018

Papers citing "Resampled Priors for Variational Autoencoders"

50 / 85 papers shown

Title
Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains Vincent Jacob Y. Diao AI4TS 46 0 0 29 Mar 2025
Studying Classifier(-Free) Guidance From a Classifier-Centric Perspective Xiaoming Zhao Alexander Schwing FaML 63 0 0 13 Mar 2025
Hierarchical VAE with a Diffusion-based VampPrior Anna Kuzina Jakub M. Tomczak DiffM TPM BDL 92 1 0 02 Dec 2024
Learning Latent Space Hierarchical EBM Diffusion Models Jiali Cui Tian Han DiffM 48 2 0 22 May 2024
You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs Yihong Luo Xiaolong Chen Xinghua Qu Jing Tang 61 6 0 19 Mar 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 36 5 0 02 Feb 2024
Matching aggregate posteriors in the variational autoencoder Surojit Saha Sarang Joshi Ross T. Whitaker DRL 37 4 0 13 Nov 2023
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning Jianxiang Feng Jongseok Lee Simon Geisler Stephan Gunnemann Rudolph Triebel OODD 32 4 0 11 Nov 2023
Reparameterized Variational Rejection Sampling M. Jankowiak Du Phan DRL BDL 24 1 0 26 Sep 2023
Diffusion Models with Deterministic Normalizing Flow Priors Mohsen Zand Ali Etemad Michael A. Greenspan DiffM 34 2 0 03 Sep 2023
On the Approximation of Bi-Lipschitz Maps by Invertible Neural Networks Bangti Jin Zehui Zhou Jun Zou 26 3 0 18 Aug 2023
Deep Probabilistic Movement Primitives with a Bayesian Aggregator Michael Przystupa Faezeh Haghverd Martin Jägersand Samuele Tosatto 21 6 0 11 Jul 2023
Unscented Autoencoder Faris Janjos Lars Rosenbaum Maxim Dolgov J. Marius Zöllner 21 2 0 08 Jun 2023
Learning Manifold Dimensions with Conditional Variational Autoencoders Yijia Zheng Tong He Yixuan Qiu David Wipf DRL 24 17 0 23 Feb 2023
The Sample Complexity of Approximate Rejection Sampling with Applications to Smoothed Online Learning Adam Block Yury Polyanskiy 39 7 0 09 Feb 2023
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes Ba-Hien Tran Babak Shahbaba Stephan Mandt Maurizio Filippone SyDa BDL UQCV 28 5 0 09 Feb 2023
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models Dongjun Kim Yeongmin Kim Se Jung Kwon Wanmo Kang Il-Chul Moon DiffM 44 86 0 28 Nov 2022
Latent Space Diffusion Models of Cryo-EM Structures Karsten Kreis Tim Dockhorn Zihao Li Ellen D. Zhong DiffM 35 15 0 25 Nov 2022
Improving Variational Autoencoders with Density Gap-based Regularization Jianfei Zhang Jun Bai Chenghua Lin Yanmeng Wang Wenge Rong DRL 36 4 0 01 Nov 2022
LION: Latent Point Diffusion Models for 3D Shape Generation Fangyin Wei Arash Vahdat Francis Williams Zan Gojcic Or Litany Sanja Fidler Karsten Kreis DiffM 73 489 0 12 Oct 2022
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders Oskar Kviman Ricky Molén A. Hotti Semih Kurt Victor Elvira J. Lagergren 32 11 0 30 Sep 2022
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model Zhisheng Xiao Tian Han 61 15 0 19 Sep 2022
A Geometric Perspective on Variational Autoencoders Clément Chadebec S. Allassonnière DRL 37 21 0 15 Sep 2022
Comparing the latent space of generative models Andrea Asperti Valerio Tonelli DRL 26 12 0 14 Jul 2022
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility Behrooz Razeghi Flavio du Pin Calmon Deniz Gunduz Slava Voloshynovskiy 29 15 0 11 Jul 2022
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case Clément Chadebec Louis J. Vincent S. Allassonnière DRL 34 29 0 16 Jun 2022
Local Distance Preserving Auto-encoders using Continuous k-Nearest Neighbours Graphs Nutan Chen Patrick van der Smagt Botond Cseke CLL 18 2 0 13 Jun 2022
Variational Sparse Coding with Learned Thresholding Kion Fallah Christopher Rozell DRL 36 7 0 07 May 2022
Particle algorithms for maximum likelihood training of latent variable models Juan Kuntz Jen Ning Lim A. M. Johansen FedML 13 21 0 27 Apr 2022
Universal approximation property of invertible neural networks Isao Ishikawa Takeshi Teshima Koichi Tojo Kenta Oono Masahiro Ikeda Masashi Sugiyama 46 29 0 15 Apr 2022
Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations Oskar Kviman Harald Melin Hazal Koptagel Victor Elvira J. Lagergren DRL 75 17 0 22 Feb 2022
VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming Eleonora Misino G. Marra Emanuele Sansone 24 21 0 07 Feb 2022
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents Kushagra Pandey Avideep Mukherjee Piyush Rai Abhishek Kumar DiffM 33 114 0 02 Jan 2022
Resampling Base Distributions of Normalizing Flows Vincent Stimper Bernhard Schölkopf José Miguel Hernández-Lobato BDL 30 32 0 29 Oct 2021
Momentum Contrastive Autoencoder: Using Contrastive Learning for Latent Space Distribution Matching in WAE Devansh Arpit Aadyot Bhatnagar Huan Wang Caiming Xiong 18 0 0 19 Oct 2021
Regularising Inverse Problems with Generative Machine Learning Models Margaret Duff Neill D. F. Campbell Matthias Joachim Ehrhardt GAN MedIm 29 34 0 22 Jul 2021
ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE Qingzhong Ai Lirong He Shiyu Liu Zenglin Xu BDL 19 2 0 20 Jul 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
Model Selection for Bayesian Autoencoders Ba-Hien Tran Simone Rossi Dimitrios Milios Pietro Michiardi Edwin V. Bonilla Maurizio Filippone BDL 23 12 0 11 Jun 2021
Score-based Generative Modeling in Latent Space Arash Vahdat Karsten Kreis Jan Kautz DiffM 16 659 0 10 Jun 2021
Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization Travers Rhodes Daniel D. Lee DRL 19 15 0 05 Jun 2021
Variational Leakage: The Role of Information Complexity in Privacy Leakage A. A. Atashin Behrooz Razeghi Deniz Gunduz Slava Voloshynovskiy PILM 16 9 0 05 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder Clément Chadebec Elina Thibeau-Sutre Ninon Burgos S. Allassonnière 38 62 0 30 Apr 2021
Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priors Fenia Christopoulou Makoto Miwa Sophia Ananiadou 43 20 0 16 Apr 2021
Variational Rejection Particle Filtering Rahul Sharma S. Banerjee Dootika Vats Piyush Rai BDL 27 0 0 29 Mar 2021
A prior-based approximate latent Riemannian metric Georgios Arvanitidis B. Georgiev Bernhard Schölkopf MedIm 14 11 0 09 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 41 483 0 08 Mar 2021
A survey on Variational Autoencoders from a GreenAI perspective Andrea Asperti David Evangelista E. Loli Piccolomini DRL 13 51 0 01 Mar 2021
GENs: Generative Encoding Networks Surojit Saha Shireen Y. Elhabian Ross T. Whitaker GAN 18 8 0 28 Oct 2020