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Inference Suboptimality in Variational Autoencoders

Inference Suboptimality in Variational Autoencoders

10 January 2018
Chris Cremer
Xuechen Li
D. Duvenaud
    DRL
    BDL
ArXivPDFHTML

Papers citing "Inference Suboptimality in Variational Autoencoders"

50 / 55 papers shown
Title
Bayesian Computation in Deep Learning
Bayesian Computation in Deep Learning
Wenlong Chen
Bolian Li
Ruqi Zhang
Yingzhen Li
BDL
75
0
0
25 Feb 2025
Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm
Nanyu Luo
Feng Ji
DRL
36
0
0
15 Feb 2025
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer
Emily C. Hector
Amanda Lenzi
41
1
0
31 Dec 2024
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
M. Valiuddin
R. V. Sloun
C.G.A. Viviers
Peter H. N. de With
Fons van der Sommen
UQCV
89
1
0
25 Nov 2024
Brain-like variational inference
Brain-like variational inference
Hadi Vafaii
Dekel Galor
Jacob L. Yates
DRL
46
0
0
25 Oct 2024
Improving Variational Autoencoder Estimation from Incomplete Data with
  Mixture Variational Families
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families
Vaidotas Šimkus
Michael U. Gutmann
35
2
0
05 Mar 2024
Domain Generalization with Small Data
Domain Generalization with Small Data
Kecheng Chen
Elena Gal
Hong Yan
Haoliang Li
OOD
19
5
0
09 Feb 2024
Variational Distribution Learning for Unsupervised Text-to-Image
  Generation
Variational Distribution Learning for Unsupervised Text-to-Image Generation
Minsoo Kang
Doyup Lee
Jiseob Kim
Saehoon Kim
Bohyung Han
DRL
OOD
14
3
0
28 Mar 2023
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via
  Bayesian Uncertainty Alignment
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via Bayesian Uncertainty Alignment
Kecheng Chen
Jie Liu
Renjie Wan
Victor Ho-Fun Lee
Varut Vardhanabhuti
Hong Yan
Haoliang Li
OOD
26
5
0
26 Feb 2023
Variational Mixture of HyperGenerators for Learning Distributions Over
  Functions
Variational Mixture of HyperGenerators for Learning Distributions Over Functions
Batuhan Koyuncu
Pablo Sánchez-Martín
I. Peis
Pablo Martínez Olmos
Isabel Valera
BDL
GAN
DRL
14
5
0
13 Feb 2023
DGNet: Distribution Guided Efficient Learning for Oil Spill Image
  Segmentation
DGNet: Distribution Guided Efficient Learning for Oil Spill Image Segmentation
Fang Chen
H. Balzter
Feixiang Zhou
Pengxin Ren
Huiyu Zhou
22
13
0
19 Dec 2022
Variational Laplace Autoencoders
Variational Laplace Autoencoders
Yookoon Park
C. Kim
Gunhee Kim
BDL
DRL
23
21
0
30 Nov 2022
Toward Adaptive Semantic Communications: Efficient Data Transmission via
  Online Learned Nonlinear Transform Source-Channel Coding
Toward Adaptive Semantic Communications: Efficient Data Transmission via Online Learned Nonlinear Transform Source-Channel Coding
Jincheng Dai
Sixian Wang
Ke Yang
Kailin Tan
Xiaoqi Qin
Zhongwei Si
K. Niu
Ping Zhang
23
19
0
08 Nov 2022
Reducing The Mismatch Between Marginal and Learned Distributions in
  Neural Video Compression
Reducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression
M. Balcilar
B. Damodaran
Pierre Hellier
15
2
0
12 Oct 2022
Variational Open-Domain Question Answering
Variational Open-Domain Question Answering
Valentin Liévin
Andreas Geert Motzfeldt
Ida Riis Jensen
Ole Winther
OOD
BDL
26
8
0
23 Sep 2022
Bit Allocation using Optimization
Bit Allocation using Optimization
Tongda Xu
Han-yi Gao
Chenjian Gao
Yuanyuan Wang
Dailan He
...
Mao Ye
Hongwei Qin
Yan Wang
Jingjing Liu
Ya-Qin Zhang
54
14
0
20 Sep 2022
Flexible Neural Image Compression via Code Editing
Flexible Neural Image Compression via Code Editing
Chenjian Gao
Tongda Xu
Dailan He
Hongwei Qin
Yan Wang
44
24
0
19 Sep 2022
A Geometric Perspective on Variational Autoencoders
A Geometric Perspective on Variational Autoencoders
Clément Chadebec
S. Allassonnière
DRL
24
21
0
15 Sep 2022
Generalization Gap in Amortized Inference
Generalization Gap in Amortized Inference
Mingtian Zhang
Peter Hayes
David Barber
BDL
CML
DRL
33
14
0
23 May 2022
Hybrid Predictive Coding: Inferring, Fast and Slow
Hybrid Predictive Coding: Inferring, Fast and Slow
Alexander Tschantz
Beren Millidge
A. Seth
Christopher L. Buckley
19
36
0
05 Apr 2022
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC
Anna Kuzina
Max Welling
Jakub M. Tomczak
AAML
DRL
31
12
0
18 Mar 2022
Model-agnostic out-of-distribution detection using combined statistical
  tests
Model-agnostic out-of-distribution detection using combined statistical tests
Federico Bergamin
Pierre-Alexandre Mattei
Jakob Drachmann Havtorn
Hugo Senetaire
Hugo Schmutz
Lars Maaløe
Søren Hauberg
J. Frellsen
OODD
21
18
0
02 Mar 2022
Tutorial on amortized optimization
Tutorial on amortized optimization
Brandon Amos
OffRL
75
43
0
01 Feb 2022
Unsupervised Representation Learning via Neural Activation Coding
Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park
Sangho Lee
Gunhee Kim
David M. Blei
SSL
19
8
0
07 Dec 2021
Counterfactual Explanations via Latent Space Projection and
  Interpolation
Counterfactual Explanations via Latent Space Projection and Interpolation
Brian Barr
Matthew R. Harrington
Samuel Sharpe
Capital One
BDL
28
10
0
02 Dec 2021
Exploring Versatile Prior for Human Motion via Motion Frequency Guidance
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
27
9
0
25 Nov 2021
Relay Variational Inference: A Method for Accelerated Encoderless VI
Relay Variational Inference: A Method for Accelerated Encoderless VI
Amir Zadeh
Santiago Benoit
Louis-Philippe Morency
DRL
12
1
0
26 Oct 2021
Meta-learning Amidst Heterogeneity and Ambiguity
Meta-learning Amidst Heterogeneity and Ambiguity
Kyeongryeol Go
Seyoung Yun
24
1
0
05 Jul 2021
ADAVI: Automatic Dual Amortized Variational Inference Applied To
  Pyramidal Bayesian Models
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models
Louis Rouillard
Demian Wassermann
28
2
0
23 Jun 2021
NeRF-VAE: A Geometry Aware 3D Scene Generative Model
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
29
139
0
01 Apr 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs,
  Normalizing Flows, Energy-Based and Autoregressive Models
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
36
478
0
08 Mar 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster
Desi R. Ivanova
Ilyas Malik
Tom Rainforth
26
78
0
03 Mar 2021
COIN: COmpression with Implicit Neural representations
COIN: COmpression with Implicit Neural representations
Emilien Dupont
Adam Goliñski
Milad Alizadeh
Yee Whye Teh
Arnaud Doucet
8
223
0
03 Mar 2021
Direct Evolutionary Optimization of Variational Autoencoders With Binary
  Latents
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents
E. Guiraud
Jakob Drefs
Jörg Lücke
DRL
27
3
0
27 Nov 2020
Neural Network-based Reconstruction in Compressed Sensing MRI Without
  Fully-sampled Training Data
Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data
Alan Q. Wang
Adrian V. Dalca
M. Sabuncu
22
26
0
29 Jul 2020
Failure Modes of Variational Autoencoders and Their Effects on
  Downstream Tasks
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
Control as Hybrid Inference
Control as Hybrid Inference
Alexander Tschantz
Beren Millidge
A. Seth
Christopher L. Buckley
19
9
0
11 Jul 2020
Bayesian Neural Networks: An Introduction and Survey
Bayesian Neural Networks: An Introduction and Survey
Ethan Goan
Clinton Fookes
BDL
UQCV
23
199
0
22 Jun 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away
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
Going in circles is the way forward: the role of recurrence in visual
  inference
Going in circles is the way forward: the role of recurrence in visual inference
R. S. V. Bergen
N. Kriegeskorte
17
81
0
26 Mar 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows
  and Latent Variable Models
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
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs
Shuyu Lin
Stephen J. Roberts
Niki Trigoni
R. Clark
DRL
13
15
0
09 Sep 2019
Independent Subspace Analysis for Unsupervised Learning of Disentangled
  Representations
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations
Jan Stühmer
Richard E. Turner
Sebastian Nowozin
DRL
BDL
CoGe
111
25
0
05 Sep 2019
Fast and Flexible Multi-Task Classification Using Conditional Neural
  Adaptive Processes
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
James Requeima
Jonathan Gordon
J. Bronskill
Sebastian Nowozin
Richard E. Turner
16
240
0
18 Jun 2019
NeoNav: Improving the Generalization of Visual Navigation via Generating
  Next Expected Observations
NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations
Qiaoyun Wu
Dinesh Manocha
Jun Wang
Kai Xu
8
15
0
17 Jun 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans
Volodimir Begy
Gilles Louppe
29
20
0
10 Mar 2019
Lagging Inference Networks and Posterior Collapse in Variational
  Autoencoders
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
Junxian He
Daniel M. Spokoyny
Graham Neubig
Taylor Berg-Kirkpatrick
BDL
DRL
8
272
0
16 Jan 2019
Bayesian Learning of Neural Network Architectures
Bayesian Learning of Neural Network Architectures
G. Dikov
Patrick van der Smagt
Justin Bayer
BDL
15
30
0
14 Jan 2019
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data
Pierre-Alexandre Mattei
J. Frellsen
SyDa
23
45
0
06 Dec 2018
Multi-Source Neural Variational Inference
Multi-Source Neural Variational Inference
Richard Kurle
Stephan Günnemann
Patrick van der Smagt
BDL
SSL
DRL
15
25
0
11 Nov 2018
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