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BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling

6 February 2019
Lars Maaløe
Marco Fraccaro
Valentin Liévin
Ole Winther
    BDL
    DRL
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Papers citing "BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling"

50 / 62 papers shown
Title
Evolved Hierarchical Masking for Self-Supervised Learning
Evolved Hierarchical Masking for Self-Supervised Learning
Zhanzhou Feng
Shiliang Zhang
49
0
0
12 Apr 2025
Your Image is Secretly the Last Frame of a Pseudo Video
Your Image is Secretly the Last Frame of a Pseudo Video
Wenlong Chen
Wenlin Chen
Lapo Rastrelli
Yingzhen Li
DiffM
VGen
34
0
0
26 Oct 2024
Diffusion Models with Deterministic Normalizing Flow Priors
Diffusion Models with Deterministic Normalizing Flow Priors
Mohsen Zand
Ali Etemad
Michael A. Greenspan
DiffM
34
2
0
03 Sep 2023
High Fidelity Image Counterfactuals with Probabilistic Causal Models
High Fidelity Image Counterfactuals with Probabilistic Causal Models
Fabio De Sousa Ribeiro
Tian Xia
M. Monteiro
Nick Pawlowski
Ben Glocker
DiffM
35
36
0
27 Jun 2023
High Fidelity Image Synthesis With Deep VAEs In Latent Space
High Fidelity Image Synthesis With Deep VAEs In Latent Space
Troy Luhman
Eric Luhman
DRL
3DV
31
7
0
23 Mar 2023
A Comprehensive Survey of AI-Generated Content (AIGC): A History of
  Generative AI from GAN to ChatGPT
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
Yihan Cao
Siyu Li
Yixin Liu
Zhiling Yan
Yutong Dai
Philip S. Yu
Lichao Sun
38
508
0
07 Mar 2023
Discouraging posterior collapse in hierarchical Variational Autoencoders
  using context
Discouraging posterior collapse in hierarchical Variational Autoencoders using context
Anna Kuzina
Jakub M. Tomczak
BDL
DRL
23
1
0
20 Feb 2023
Where to Diffuse, How to Diffuse, and How to Get Back: Automated
  Learning for Multivariate Diffusions
Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions
Raghav Singhal
Mark Goldstein
Rajesh Ranganath
DiffM
39
21
0
14 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
25
5
0
13 Feb 2023
A Multi-Resolution Framework for U-Nets with Applications to
  Hierarchical VAEs
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs
Fabian Falck
Christopher Williams
D. Danks
George Deligiannidis
C. Yau
Chris Holmes
Arnaud Doucet
M. Willetts
36
8
0
19 Jan 2023
Long-horizon video prediction using a dynamic latent hierarchy
Long-horizon video prediction using a dynamic latent hierarchy
Alexey Zakharov
Qinghai Guo
Z. Fountas
31
4
0
29 Dec 2022
Scaling Up Probabilistic Circuits by Latent Variable Distillation
Scaling Up Probabilistic Circuits by Latent Variable Distillation
Guy Van den Broeck
Honghua Zhang
Mathias Niepert
TPM
25
24
0
10 Oct 2022
GFlowNets and variational inference
GFlowNets and variational inference
Nikolay Malkin
Salem Lahlou
T. Deleu
Xu Ji
J. E. Hu
Katie Everett
Dinghuai Zhang
Yoshua Bengio
BDL
134
77
0
02 Oct 2022
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image
  Fusion
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion
Fabian Duffhauss
Ngo Anh Vien
Hanna Ziesche
Gerhard Neumann
38
4
0
22 Sep 2022
Fast Lossless Neural Compression with Integer-Only Discrete Flows
Fast Lossless Neural Compression with Integer-Only Discrete Flows
Siyu Wang
Jianfei Chen
Chongxuan Li
Jun Zhu
Bo Zhang
MQ
26
7
0
17 Jun 2022
Top-down inference in an early visual cortex inspired hierarchical
  Variational Autoencoder
Top-down inference in an early visual cortex inspired hierarchical Variational Autoencoder
F. Csikor
B. Meszéna
Bence Szabó
Gergő Orbán
BDL
DRL
27
5
0
01 Jun 2022
Few-Shot Diffusion Models
Few-Shot Diffusion Models
Giorgio Giannone
Didrik Nielsen
Ole Winther
DiffM
186
49
0
30 May 2022
Novel Applications for VAE-based Anomaly Detection Systems
Novel Applications for VAE-based Anomaly Detection Systems
Luca Bergamin
Tommaso Carraro
Mirko Polato
F. Aiolli
DRL
24
6
0
26 Apr 2022
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality
  Speech Synthesis
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis
Max W. Y. Lam
Jun Wang
Dan Su
Dong Yu
DiffM
36
92
0
25 Mar 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
Image Super-Resolution With Deep Variational Autoencoders
Image Super-Resolution With Deep Variational Autoencoders
Darius Chira
Ilian Haralampiev
Ole Winther
Andrea Dittadi
Valentin Liévin
DRL
35
32
0
17 Mar 2022
Long Document Summarization with Top-down and Bottom-up Inference
Long Document Summarization with Top-down and Bottom-up Inference
Bo Pang
Erik Nijkamp
Wojciech Kry'sciñski
Silvio Savarese
Yingbo Zhou
Caiming Xiong
RALM
BDL
24
55
0
15 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
24
18
0
02 Mar 2022
Benchmarking Generative Latent Variable Models for Speech
Benchmarking Generative Latent Variable Models for Speech
Jakob Drachmann Havtorn
Lasse Borgholt
Søren Hauberg
J. Frellsen
Lars Maaløe
26
3
0
22 Feb 2022
Missing Data Imputation and Acquisition with Deep Hierarchical Models
  and Hamiltonian Monte Carlo
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo
I. Peis
Chao Ma
José Miguel Hernández-Lobato
BDL
DRL
16
14
0
09 Feb 2022
VAEL: Bridging Variational Autoencoders and Probabilistic Logic
  Programming
VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming
Eleonora Misino
G. Marra
Emanuele Sansone
24
21
0
07 Feb 2022
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Katie Z Luo
Guandao Yang
Wenqi Xian
Harald Haraldsson
B. Hariharan
Serge Belongie
DiffM
23
5
0
01 Feb 2022
Out of Distribution Detection on ImageNet-O
Out of Distribution Detection on ImageNet-O
Anugya Srivastava
S. Jain
Mugdha Thigle
OOD
57
5
0
23 Jan 2022
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample
  Generation on the Boundary
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary
Nikolaos Dionelis
Mehrdad Yaghoobi
Sotirios A. Tsaftaris
OODD
23
6
0
28 Oct 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using
  Vector Quantization
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
Mucong Ding
Kezhi Kong
Jingling Li
Chen Zhu
John P. Dickerson
Furong Huang
Tom Goldstein
GNN
MQ
33
47
0
27 Oct 2021
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs
  Theory
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
Bilateral Denoising Diffusion Models
Bilateral Denoising Diffusion Models
Max W. Y. Lam
Jun Wang
Rongjie Huang
Dan Su
Dong Yu
DiffM
27
42
0
26 Aug 2021
ImageBART: Bidirectional Context with Multinomial Diffusion for
  Autoregressive Image Synthesis
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis
Patrick Esser
Robin Rombach
A. Blattmann
Bjorn Ommer
DiffM
38
156
0
19 Aug 2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network
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
38
0
30 Jun 2021
The Values Encoded in Machine Learning Research
The Values Encoded in Machine Learning Research
Abeba Birhane
Pratyusha Kalluri
Dallas Card
William Agnew
Ravit Dotan
Michelle Bao
41
274
0
29 Jun 2021
Score-based Generative Modeling in Latent Space
Score-based Generative Modeling in Latent Space
Arash Vahdat
Karsten Kreis
Jan Kautz
DiffM
16
659
0
10 Jun 2021
On Training Sample Memorization: Lessons from Benchmarking Generative
  Modeling with a Large-scale Competition
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition
C. Bai
Hsuan-Tien Lin
Colin Raffel
Wendy Kan
18
34
0
06 Jun 2021
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial
  Attacks
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks
Anna Kuzina
Max Welling
Jakub M. Tomczak
AAML
DRL
36
10
0
10 Mar 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
41
481
0
08 Mar 2021
Greedy Hierarchical Variational Autoencoders for Large-Scale Video
  Prediction
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
Bohan Wu
Suraj Nair
Roberto Martin-Martin
Li Fei-Fei
Chelsea Finn
DRL
27
99
0
06 Mar 2021
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them
  on Images
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images
R. Child
BDL
VLM
56
337
0
20 Nov 2020
Reducing the Computational Cost of Deep Generative Models with Binary
  Neural Networks
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks
Thomas Bird
F. Kingma
David Barber
SyDa
MQ
AI4CE
26
9
0
26 Oct 2020
Further Analysis of Outlier Detection with Deep Generative Models
Further Analysis of Outlier Detection with Deep Generative Models
Ziyu Wang
Bin Dai
David Wipf
Jun Zhu
17
39
0
25 Oct 2020
A Quaternion-Valued Variational Autoencoder
A Quaternion-Valued Variational Autoencoder
Eleonora Grassucci
Danilo Comminiello
A. Uncini
DRL
28
21
0
22 Oct 2020
Conditional Generative Modeling via Learning the Latent Space
Conditional Generative Modeling via Learning the Latent Space
Sameera Ramasinghe
Kanchana Ranasinghe
Salman Khan
Nick Barnes
Stephen Gould
BDL
31
9
0
07 Oct 2020
Self-Supervised Variational Auto-Encoders
Self-Supervised Variational Auto-Encoders
Ioannis Gatopoulos
Jakub M. Tomczak
32
13
0
05 Oct 2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with
  Reliable Uncertainty Estimation
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation
Xuming Ran
Mingkun Xu
Lingrui Mei
Qi Xu
Quanying Liu
OODD
UQCV
42
50
0
16 Jul 2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless
  Compression
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression
Rianne van den Berg
A. Gritsenko
Mostafa Dehghani
C. Sønderby
Tim Salimans
27
59
0
22 Jun 2020
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
118
17,042
0
19 Jun 2020
Capturing Label Characteristics in VAEs
Capturing Label Characteristics in VAEs
Thomas Joy
Sebastian M. Schmon
Philip Torr
N. Siddharth
Tom Rainforth
CML
DRL
30
43
0
17 Jun 2020
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