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Learning Hierarchical Features from Generative Models
v1v2 (latest)

Learning Hierarchical Features from Generative Models

27 February 2017
Shengjia Zhao
Jiaming Song
Stefano Ermon
    BDLGANOODDRL
ArXiv (abs)PDFHTML

Papers citing "Learning Hierarchical Features from Generative Models"

50 / 50 papers shown
Contrastive Deep Learning for Variant Detection in Wastewater Genomic Sequencing
Contrastive Deep Learning for Variant Detection in Wastewater Genomic Sequencing
Adele Chinda
Richmond Azumah
Hemanth Demakethepalli Venkateswara
100
0
0
02 Dec 2025
Likelihood-Free Variational Autoencoders
Likelihood-Free Variational Autoencoders
Chen Xu
Qiang Wang
Lijun Sun
DiffMDRL
605
0
0
24 Apr 2025
Evolved Hierarchical Masking for Self-Supervised Learning
Evolved Hierarchical Masking for Self-Supervised LearningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
Zhanzhou Feng
Shiliang Zhang
405
1
0
12 Apr 2025
Scale-wise Distillation of Diffusion Models
Scale-wise Distillation of Diffusion Models
Nikita Starodubcev
Denis Kuznedelev
Artem Babenko
Dmitry Baranchuk
Dmitry Baranchuk
DiffM
385
6
0
20 Mar 2025
Nested Diffusion Models Using Hierarchical Latent Priors
Nested Diffusion Models Using Hierarchical Latent PriorsComputer Vision and Pattern Recognition (CVPR), 2024
Xiao Zhang
Ruoxi Jiang
Rebecca Willett
Michael Maire
BDLDiffM
402
2
0
08 Dec 2024
CAVACHON: a hierarchical variational autoencoder to integrate
  multi-modal single-cell data
CAVACHON: a hierarchical variational autoencoder to integrate multi-modal single-cell data
Ping-Han Hsieh
Ru-Xiu Hsiao
Katalin Ferenc
Anthony Mathelier
R. Burkholz
Chien-Yu Chen
G. K. Sandve
T. Belova
M. Kuijjer
175
0
0
28 May 2024
Learning Latent Space Hierarchical EBM Diffusion Models
Learning Latent Space Hierarchical EBM Diffusion Models
Jiali Cui
Tian Han
DiffM
502
7
0
22 May 2024
Learning Hierarchical Features with Joint Latent Space Energy-Based
  Prior
Learning Hierarchical Features with Joint Latent Space Energy-Based Prior
Jiali Cui
Ying Nian Wu
Tian Han
BDL
208
11
0
14 Oct 2023
Learning Joint Latent Space EBM Prior Model for Multi-layer Generator
Learning Joint Latent Space EBM Prior Model for Multi-layer GeneratorComputer Vision and Pattern Recognition (CVPR), 2023
Jiali Cui
Ying Nian Wu
Tian Han
288
13
0
10 Jun 2023
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in
  Conditional and Hierarchical Variational Autoencoders
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational AutoencodersInternational Conference on Learning Representations (ICLR), 2023
Hien Dang
Tho Tran
T. Nguyen
Nhat Ho
CMLDRL
465
8
0
08 Jun 2023
Understanding Masked Autoencoders via Hierarchical Latent Variable
  Models
Understanding Masked Autoencoders via Hierarchical Latent Variable ModelsComputer Vision and Pattern Recognition (CVPR), 2023
Lingjing Kong
Martin Q. Ma
Guan-Hong Chen
Eric Xing
Yuejie Chi
Louis-Philippe Morency
Kun Zhang
276
49
0
08 Jun 2023
Multifactor Sequential Disentanglement via Structured Koopman
  Autoencoders
Multifactor Sequential Disentanglement via Structured Koopman AutoencodersInternational Conference on Learning Representations (ICLR), 2023
Nimrod Berman
Ilana D Naiman
Omri Azencot
CoGe
259
28
0
30 Mar 2023
Computing with Categories in Machine Learning
Computing with Categories in Machine LearningArtificial General Intelligence (AGI), 2023
Eli Sennesh
T. Xu
Yoshihiro Maruyama
350
2
0
07 Mar 2023
Deep Clustering: A Comprehensive Survey
Deep Clustering: A Comprehensive SurveyIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Yazhou Ren
Jingyu Pu
Zhimeng Yang
Jie Xu
Guofeng Li
X. Pu
Philip S. Yu
Lifang He
HAI
400
225
0
09 Oct 2022
Gromov-Wasserstein Autoencoders
Gromov-Wasserstein AutoencodersInternational Conference on Learning Representations (ICLR), 2022
Nao Nakagawa
Ren Togo
Takahiro Ogawa
Miki Haseyama
GANDRL
297
17
0
15 Sep 2022
A Probabilistic Generative Model of Free Categories
A Probabilistic Generative Model of Free Categories
Eli Sennesh
T. Xu
Y. Maruyama
307
0
0
09 May 2022
Multi-Task Neural Processes
Multi-Task Neural Processes
Jiayi Shen
Xiantong Zhen
M. Worring
Ling Shao
BDL
332
9
0
10 Nov 2021
Learning Interpretable Representations of Entanglement in Quantum Optics
  Experiments using Deep Generative Models
Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative ModelsNature Machine Intelligence (Nat. Mach. Intell.), 2021
Daniel Flam-Shepherd
Tony C Wu
Xuemei Gu
Alba Cervera-Lierta
Mario Krenn
Alán Aspuru-Guzik
DRL
190
27
0
06 Sep 2021
Unsupervised Learning of Neurosymbolic Encoders
Unsupervised Learning of Neurosymbolic Encoders
Eric Zhan
Jennifer J. Sun
Ann Kennedy
Yisong Yue
Swarat Chaudhuri
283
16
0
28 Jul 2021
Meta-learning Amidst Heterogeneity and Ambiguity
Meta-learning Amidst Heterogeneity and Ambiguity
Kyeongryeol Go
Seyoung Yun
294
1
0
05 Jul 2021
On Incorporating Inductive Biases into VAEs
On Incorporating Inductive Biases into VAEsInternational Conference on Learning Representations (ICLR), 2021
Ning Miao
Emile Mathieu
N. Siddharth
Yee Whye Teh
Tom Rainforth
CMLDRL
294
11
0
25 Jun 2021
Commutative Lie Group VAE for Disentanglement Learning
Commutative Lie Group VAE for Disentanglement LearningInternational Conference on Machine Learning (ICML), 2021
Xinqi Zhu
Chang Xu
Dacheng Tao
CoGeDRL
250
34
0
07 Jun 2021
Where and What? Examining Interpretable Disentangled Representations
Where and What? Examining Interpretable Disentangled RepresentationsComputer Vision and Pattern Recognition (CVPR), 2021
Xinqi Zhu
Chang Xu
Dacheng Tao
FAttDRL
271
48
0
07 Apr 2021
Diagonal Attention and Style-based GAN for Content-Style Disentanglement
  in Image Generation and Translation
Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and TranslationIEEE International Conference on Computer Vision (ICCV), 2021
Gihyun Kwon
Jong Chul Ye
450
60
0
30 Mar 2021
Greedy Hierarchical Variational Autoencoders for Large-Scale Video
  Prediction
Greedy Hierarchical Variational Autoencoders for Large-Scale Video PredictionComputer Vision and Pattern Recognition (CVPR), 2021
Bohan Wu
Suraj Nair
Roberto Martin-Martin
Li Fei-Fei
Chelsea Finn
DRL
454
118
0
06 Mar 2021
Clockwork Variational Autoencoders
Clockwork Variational AutoencodersNeural Information Processing Systems (NeurIPS), 2021
Vaibhav Saxena
Jimmy Ba
Danijar Hafner
VGenDRL
289
59
0
18 Feb 2021
Learning a Deep Generative Model like a Program: the Free Category Prior
Learning a Deep Generative Model like a Program: the Free Category Prior
Eli Sennesh
NAIBDL
203
0
0
22 Nov 2020
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them
  on Images
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on ImagesInternational Conference on Learning Representations (ICLR), 2020
R. Child
BDLVLM
579
394
0
20 Nov 2020
Learning Disentangled Representations with Latent Variation
  Predictability
Learning Disentangled Representations with Latent Variation PredictabilityEuropean Conference on Computer Vision (ECCV), 2020
Xinqi Zhu
Chang Xu
Dacheng Tao
CoGeDRL
299
27
0
25 Jul 2020
Relaxed-Responsibility Hierarchical Discrete VAEs
Relaxed-Responsibility Hierarchical Discrete VAEs
M. Willetts
Xenia Miscouridou
Stephen J. Roberts
Chris Holmes
BDLDRL
303
5
0
14 Jul 2020
An Explicit Local and Global Representation Disentanglement Framework
  with Applications in Deep Clustering and Unsupervised Object Detection
An Explicit Local and Global Representation Disentanglement Framework with Applications in Deep Clustering and Unsupervised Object Detection
Rujikorn Charakorn
Y. Thawornwattana
Sirawaj Itthipuripat
Nick Pawlowski
P. Manoonpong
Nat Dilokthanakul
DRLOCL
288
13
0
24 Jan 2020
There and Back Again: Unraveling the Variational Auto-Encoder
There and Back Again: Unraveling the Variational Auto-Encoder
Graham Fyffe
DRL
185
0
0
21 Dec 2019
High- and Low-level image component decomposition using VAEs for
  improved reconstruction and anomaly detection
High- and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection
David Zimmerer
Jens Petersen
Klaus Maier-Hein
DRL
179
8
0
27 Nov 2019
Disentangling to Cluster: Gaussian Mixture Variational Ladder
  Autoencoders
Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders
M. Willetts
Stephen J. Roberts
Chris Holmes
CoGeDRL
186
17
0
25 Sep 2019
Improving VAEs' Robustness to Adversarial Attack
Improving VAEs' Robustness to Adversarial Attack
M. Willetts
A. Camuto
Tom Rainforth
Stephen J. Roberts
Chris Holmes
DRLAAML
567
5
0
01 Jun 2019
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with
  Hierarchical Latent Variables
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent VariablesInternational Conference on Machine Learning (ICML), 2019
F. Kingma
Pieter Abbeel
Jonathan Ho
424
110
0
16 May 2019
Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent
  Speech Interfaces
Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent Speech Interfaces
G. Gosztolya
Á. Pintér
L. Tóth
Tamás Grósz
Alexandra Markó
T. Csapó
163
17
0
10 Apr 2019
FAVAE: Sequence Disentanglement using Information Bottleneck Principle
FAVAE: Sequence Disentanglement using Information Bottleneck Principle
Masanori Yamada
Heecheol Kim
Kosuke Miyoshi
Hiroshi Yamakawa
CMLDRLCoGe
167
6
0
22 Feb 2019
STCN: Stochastic Temporal Convolutional Networks
STCN: Stochastic Temporal Convolutional Networks
Emre Aksan
Otmar Hilliges
BDL
294
65
0
18 Feb 2019
Latent Variable Modeling for Generative Concept Representations and Deep
  Generative Models
Latent Variable Modeling for Generative Concept Representations and Deep Generative Models
Daniel T. Chang
DRLBDL
134
4
0
26 Dec 2018
A Tutorial on Deep Latent Variable Models of Natural Language
A Tutorial on Deep Latent Variable Models of Natural Language
Yoon Kim
Sam Wiseman
Alexander M. Rush
BDLVLM
363
46
0
17 Dec 2018
Context-encoding Variational Autoencoder for Unsupervised Anomaly
  Detection
Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection
David Zimmerer
Simon A. A. Kohl
Jens Petersen
Hyunjin Park
Klaus H. Maier-Hein
DRL
304
142
0
14 Dec 2018
Rare Event Detection using Disentangled Representation Learning
Rare Event Detection using Disentangled Representation Learning
Ryuhei Hamaguchi
Ken Sakurada
Ryosuke Nakamura
DRL
270
38
0
04 Dec 2018
An Interpretable Generative Model for Handwritten Digit Image Synthesis
An Interpretable Generative Model for Handwritten Digit Image Synthesis
Yao Zhu
Saksham Suri
Pranav Kulkarni
Yueru Chen
Jiali Duan
C.-C. Jay Kuo
GAN
164
4
0
11 Nov 2018
Generation Meets Recommendation: Proposing Novel Items for Groups of
  Users
Generation Meets Recommendation: Proposing Novel Items for Groups of Users
Thanh Vinh Vo
Harold Soh
VGen
146
24
0
02 Aug 2018
Generative Adversarial Image Synthesis with Decision Tree Latent
  Controller
Generative Adversarial Image Synthesis with Decision Tree Latent Controller
Takuhiro Kaneko
Kaoru Hiramatsu
K. Kashino
194
25
0
27 May 2018
Degeneration in VAE: in the Light of Fisher Information Loss
Degeneration in VAE: in the Light of Fisher Information Loss
Huangjie Zheng
Jiangchao Yao
Ya Zhang
Ivor W. Tsang
DRL
211
18
0
19 Feb 2018
Auto-Encoding Total Correlation Explanation
Auto-Encoding Total Correlation Explanation
Shuyang Gao
Rob Brekelmans
Greg Ver Steeg
Aram Galstyan
BDLDRL
281
84
0
16 Feb 2018
Deep Neural Generative Model of Functional MRI Images for Psychiatric
  Disorder Diagnosis
Deep Neural Generative Model of Functional MRI Images for Psychiatric Disorder Diagnosis
Takashi Matsubara
T. Tashiro
K. Uehara
MedIm
132
45
0
18 Dec 2017
InfoVAE: Information Maximizing Variational Autoencoders
InfoVAE: Information Maximizing Variational Autoencoders
Shengjia Zhao
Jiaming Song
Stefano Ermon
DRL
628
482
0
07 Jun 2017
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