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Diagnosing and Enhancing VAE Models

14 March 2019

Papers citing "Diagnosing and Enhancing VAE Models"

50 / 242 papers shown

Title
Particle algorithms for maximum likelihood training of latent variable models Juan Kuntz Jen Ning Lim A. M. Johansen FedML 121 23 0 27 Apr 2022
Diagnosing and Fixing Manifold Overfitting in Deep Generative Models Gabriel Loaiza-Ganem Brendan Leigh Ross Jesse C. Cresswell Anthony L. Caterini GAN DRL 104 31 0 14 Apr 2022
Learning and controlling the source-filter representation of speech with a variational autoencoder Samir Sadok Simon Leglaive Laurent Girin Xavier Alameda-Pineda Renaud Séguier SSL DRL BDL 115 14 0 14 Apr 2022
Pixel VQ-VAEs for Improved Pixel Art Representation Akash Saravanan Matthew J. Guzdial 54 8 0 23 Mar 2022
VQ-Flows: Vector Quantized Local Normalizing Flows Sahil Sidheekh Chris B. Dock Tushar Jain R. Balan M. Singh 65 8 0 22 Mar 2022
AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-Decoder Yunseung Lee Pilsung Kang ViT 85 77 0 21 Mar 2022
The Transitive Information Theory and its Application to Deep Generative Models Trung Ngo Trong Najwa Laabid Ville Hautamaki M. Heinäniemi DRL 95 0 0 09 Mar 2022
Variational Autoencoders Without the Variation Gregory A. Daly J. Fieldsend G. Tabor 63 2 0 01 Mar 2022
Exact Solutions of a Deep Linear Network Liu Ziyin Botao Li Xiangmin Meng ODL 88 22 0 10 Feb 2022
Enhancing variational generation through self-decomposition Andrea Asperti Laura Bugo Daniele Filippini DRL 95 2 0 06 Feb 2022
Direct Molecular Conformation Generation Jinhua Zhu Yingce Xia Chang-Shu Liu Lijun Wu Shufang Xie ... Tao Qin Wen-gang Zhou Houqiang Li Haiguang Liu Tie-Yan Liu 85 42 0 03 Feb 2022
Stochastic Neural Networks with Infinite Width are Deterministic Liu Ziyin Hanlin Zhang Xiangming Meng Yuting Lu Eric P. Xing Masakuni Ueda 93 3 0 30 Jan 2022
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents Kushagra Pandey Avideep Mukherjee Piyush Rai Abhishek Kumar DiffM 117 121 0 02 Jan 2022
Beta-VAE Reproducibility: Challenges and Extensions M. Fil Munib Mesinovic Matthew Morris J. Wildberger DRL 39 9 0 28 Dec 2021
Generating Synthetic Mixed-type Longitudinal Electronic Health Records for Artificial Intelligent Applications Jin Li B. Cairns Jingsong Li T. Zhu SyDa 87 77 0 22 Dec 2021
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 603 15,845 0 20 Dec 2021
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias Frederic Koehler Viraj Mehta Chenghui Zhou Andrej Risteski DRL 87 13 0 13 Dec 2021
Face Reconstruction with Variational Autoencoder and Face Masks Rafael S. Toledo Eric A. Antonelo CVBM 3DH 17 3 0 03 Dec 2021
Forward Operator Estimation in Generative Models with Kernel Transfer Operators Z. Huang Rudrasis Chakraborty Vikas Singh GAN 50 3 0 01 Dec 2021
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 94 25 0 24 Nov 2021
Momentum Contrastive Autoencoder: Using Contrastive Learning for Latent Space Distribution Matching in WAE Devansh Arpit Aadyot Bhatnagar Huan Wang Caiming Xiong 40 0 0 19 Oct 2021
Spread Flows for Manifold Modelling Mingtian Zhang Yitong Sun Chen Zhang Jingyu Sun AI4CE 51 2 0 29 Sep 2021
Be More Active! Understanding the Differences between Mean and Sampled Representations of Variational Autoencoders Lisa Bonheme M. Grzes DRL 79 6 0 26 Sep 2021
LDC-VAE: A Latent Distribution Consistency Approach to Variational AutoEncoders Xiaoyu Chen Chen Gong Qiang He Xinwen Hou Yu Liu 72 1 0 22 Sep 2021
Sentence Bottleneck Autoencoders from Transformer Language Models Ivan Montero Nikolaos Pappas Noah A. Smith AI4CE 81 29 0 31 Aug 2021
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis Patrick Esser Robin Rombach A. Blattmann Bjorn Ommer DiffM 110 162 0 19 Aug 2021
SynFace: Face Recognition with Synthetic Data Haibo Qiu Baosheng Yu Dihong Gong Zhifeng Li Wei Liu Dacheng Tao 116 129 0 18 Aug 2021
Redatuming physical systems using symmetric autoencoders P. Bharadwaj Matthew T.C. Li L. Demanet 56 4 0 05 Aug 2021
Regularising Inverse Problems with Generative Machine Learning Models Margaret Duff Neill D. F. Campbell Matthias Joachim Ehrhardt GAN MedIm 67 38 0 22 Jul 2021
The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders Divyansh Pareek Andrej Risteski DRL 50 0 0 09 Jul 2021
Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb Stefan Bauer M. Besserve Bernhard Schölkopf DRL 93 18 0 30 Jun 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
Re-parameterizing VAEs for stability David Dehaene Rémy Brossard DRL 68 9 0 25 Jun 2021
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation Xiaohui Zeng R. Urtasun R. Zemel Sanja Fidler Renjie Liao DiffM 36 2 0 25 Jun 2021
Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation Magda Amiridi Nikos Kargas N. Sidiropoulos 113 11 0 20 Jun 2021
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation Abhishek Sinha Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 132 121 0 12 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
Score-based Generative Modeling in Latent Space Arash Vahdat Karsten Kreis Jan Kautz DiffM 89 688 0 10 Jun 2021
Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows Brendan Leigh Ross Jesse C. Cresswell TPM 85 32 0 09 Jun 2021
Rectangular Flows for Manifold Learning Anthony L. Caterini Gabriel Loaiza-Ganem Geoff Pleiss John P. Cunningham DRL 109 47 0 02 Jun 2021
Latent Space Refinement for Deep Generative Models R. Winterhalder Marco Bellagente Benjamin Nachman BDL GAN DRL DiffM 126 27 0 01 Jun 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 129 69 0 30 Apr 2021
Eccentric Regularization: Minimizing Hyperspherical Energy without explicit projection Xuefeng Li Alan Blair 53 0 0 23 Apr 2021
Geometry-Free View Synthesis: Transformers and no 3D Priors Robin Rombach Patrick Esser Bjorn Ommer ViT 103 95 0 15 Apr 2021
Neighbor Embedding Variational Autoencoder Renfei Tu Yang Liu Yongzeng Xue Cheng Wang Maozu Guo BDL DRL 60 0 0 21 Mar 2021
VDSM: Unsupervised Video Disentanglement with State-Space Modeling and Deep Mixtures of Experts M. Vowels Necati Cihan Camgöz Richard Bowden CoGe 87 8 0 12 Mar 2021
A prior-based approximate latent Riemannian metric Georgios Arvanitidis B. Georgiev Bernhard Schölkopf MedIm 60 13 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 176 508 0 08 Mar 2021
Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior Mario González Andrés Almansa Pauline Tan 92 31 0 02 Mar 2021
A survey on Variational Autoencoders from a GreenAI perspective Andrea Asperti David Evangelista E. Loli Piccolomini DRL 91 52 0 01 Mar 2021