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1805.08913
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Amortized Inference Regularization
23 May 2018
Rui Shu
Hung Bui
Shengjia Zhao
Mykel J. Kochenderfer
Stefano Ermon
DRL
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Papers citing
"Amortized Inference Regularization"
50 / 53 papers shown
On The Finetuning of MLIPs Through the Lens of Iterated Maps With BPTT
Evan Dramko
Yizhi Zhu
Aleksandar Krivokapic
Geoffroy Hautier
Thomas Reps
C. Jermaine
Anastasios Kyrillidis
155
0
0
30 Nov 2025
Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework without Data
Journal of Chemical Theory and Computation (JCTC), 2025
Maximilian Stupp
P. S. Koutsourelakis
420
2
0
29 Apr 2025
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse Problems
Sojin Lee
Dogyun Park
Inho Kong
Hyunwoo J. Kim
DiffM
309
12
0
23 Jul 2024
Amortized Variational Inference: When and Why?
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
C. Margossian
David M. Blei
454
26
0
20 Jul 2023
Revisiting Structured Variational Autoencoders
International Conference on Machine Learning (ICML), 2023
Yixiu Zhao
Scott W. Linderman
BDL
DRL
324
14
0
25 May 2023
Adversarial robustness of amortized Bayesian inference
International Conference on Machine Learning (ICML), 2023
Manuel Glöckler
Michael Deistler
Jakob H. Macke
AAML
351
23
0
24 May 2023
Amortized Variational Inference: A Systematic Review
Journal of Artificial Intelligence Research (JAIR), 2022
Ankush Ganguly
Sanjana Jain
Ukrit Watchareeruetai
311
33
0
22 Sep 2022
Langevin Autoencoders for Learning Deep Latent Variable Models
Neural Information Processing Systems (NeurIPS), 2022
Shohei Taniguchi
Yusuke Iwasawa
Wataru Kumagai
Yutaka Matsuo
BDL
SyDa
355
2
0
15 Sep 2022
Revisiting Active Sets for Gaussian Process Decoders
Neural Information Processing Systems (NeurIPS), 2022
Pablo Moreno-Muñoz
Cilie W. Feldager
Søren Hauberg
293
4
0
10 Sep 2022
Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models
International Conference on Learning Representations (ICLR), 2022
Yong Zhong
Hongtao Liu
Xiaodong Liu
Fan Bao
Weiran Shen
Chongxuan Li
AI4CE
341
7
0
30 Aug 2022
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
Neural Information Processing Systems (NeurIPS), 2022
Patrik Reizinger
Luigi Gresele
Jack Brady
Julius von Kügelgen
Dominik Zietlow
Bernhard Schölkopf
Georg Martius
Wieland Brendel
M. Besserve
DRL
442
28
0
06 Jun 2022
Improving VAE-based Representation Learning
Mingtian Zhang
Tim Z. Xiao
Brooks Paige
David Barber
SSL
DRL
309
14
0
28 May 2022
Generalization Gap in Amortized Inference
Neural Information Processing Systems (NeurIPS), 2022
Mingtian Zhang
Peter Hayes
David Barber
BDL
CML
DRL
363
14
0
23 May 2022
On PAC-Bayesian reconstruction guarantees for VAEs
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Badr-Eddine Chérief-Abdellatif
Yuyang Shi
Arnaud Doucet
Benjamin Guedj
DRL
324
23
0
23 Feb 2022
Computing Multiple Image Reconstructions with a Single Hypernetwork
Machine Learning for Biomedical Imaging (MLBI), 2022
Alan Q. Wang
Adrian Dalca
M. Sabuncu
529
10
0
22 Feb 2022
An Introduction to Variational Inference
Ankush Ganguly
Samuel W. F. Earp
BDL
324
27
0
30 Aug 2021
FastSHAP: Real-Time Shapley Value Estimation
International Conference on Learning Representations (ICLR), 2021
Hao Zhang
Mukund Sudarshan
Ian Covert
Su-In Lee
Rajesh Ranganath
TDI
FAtt
493
183
0
15 Jul 2021
Input Dependent Sparse Gaussian Processes
International Conference on Machine Learning (ICML), 2021
B. Jafrasteh
Carlos Villacampa-Calvo
Daniel Hernández-Lobato
UQCV
293
7
0
15 Jul 2021
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models
Louis Rouillard
Demian Wassermann
261
2
0
23 Jun 2021
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
M. Willetts
Brooks Paige
CML
OOD
392
28
0
09 Jun 2021
Variational Autoencoders: A Harmonic Perspective
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
A. Camuto
M. Willetts
DRL
273
3
0
31 May 2021
Partition Function Estimation: A Quantitative Study
International Joint Conference on Artificial Intelligence (IJCAI), 2021
Durgesh Kumar Agrawal
Yash Pote
Kuldeep S. Meel
255
13
0
24 May 2021
Modeling Graph Node Correlations with Neighbor Mixture Models
Linfeng Liu
Michael Hughes
Liping Liu
318
0
0
29 Mar 2021
VAE Approximation Error: ELBO and Exponential Families
International Conference on Learning Representations (ICLR), 2021
Alexander Shekhovtsov
D. Schlesinger
B. Flach
DRL
238
21
0
18 Feb 2021
Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks
Alan Q. Wang
Adrian Dalca
M. Sabuncu
OOD
228
14
0
06 Jan 2021
Mutual Information Constraints for Monte-Carlo Objectives
Journal of machine learning research (JMLR), 2020
Gábor Melis
András Gyorgy
Phil Blunsom
327
1
0
01 Dec 2020
Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
Junwen Bai
Weiran Wang
Yingbo Zhou
Caiming Xiong
SSL
AI4TS
262
12
0
07 Oct 2020
Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data
Alan Q. Wang
Adrian Dalca
M. Sabuncu
365
28
0
29 Jul 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks
Yaniv Yacoby
Weiwei Pan
Finale Doshi-Velez
CML
DRL
542
32
0
14 Jul 2020
Simple and Effective VAE Training with Calibrated Decoders
International Conference on Machine Learning (ICML), 2020
Oleh Rybkin
Kostas Daniilidis
Sergey Levine
394
117
0
23 Jun 2020
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip
AAAI Conference on Artificial Intelligence (AAAI), 2020
Yuxuan Song
Minkai Xu
Lantao Yu
Hao Zhou
Shuo Shao
Yong Yu
AAML
196
17
0
03 Apr 2020
On Implicit Regularization in
β
β
β
-VAEs
International Conference on Machine Learning (ICML), 2020
Abhishek Kumar
Ben Poole
DRL
768
59
0
31 Jan 2020
RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback
Web Search and Data Mining (WSDM), 2019
Ilya Shenbin
Anton M. Alekseev
E. Tutubalina
Valentin Malykh
Sergey I. Nikolenko
BDL
DRL
336
255
0
24 Dec 2019
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection
Erik A. Daxberger
José Miguel Hernández-Lobato
UQCV
487
67
0
11 Dec 2019
Rate-Regularization and Generalization in VAEs
Alican Bozkurt
Babak Esmaeili
Jean-Baptiste Tristan
Dana H. Brooks
Jennifer G. Dy
Jan-Willem van de Meent
DRL
475
8
0
11 Nov 2019
"Best-of-Many-Samples" Distribution Matching
Apratim Bhattacharyya
Mario Fritz
Bernt Schiele
GAN
DRL
152
4
0
27 Sep 2019
Variational Bayesian Context-aware Representation for Grocery Recommendation
Zaiqiao Meng
R. McCreadie
Craig Macdonald
I. Ounis
BDL
CML
231
7
0
17 Sep 2019
Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks
Juan Maroñas
Roberto Paredes Palacios
D. Ramos-Castro
UQCV
BDL
337
30
0
23 Aug 2019
Product Aesthetic Design: A Machine Learning Augmentation
Marketing science (Providence, R.I.) (MSPRI), 2019
Alex Burnap
J. Hauser
Artem Timoshenko
177
69
0
17 Jul 2019
Towards Amortized Ranking-Critical Training for Collaborative Filtering
Sam Lobel
Chunyuan Li
Jianfeng Gao
Lawrence Carin
271
19
0
10 Jun 2019
Multi-objects Generation with Amortized Structural Regularization
Neural Information Processing Systems (NeurIPS), 2019
Kun Xu
Chongxuan Li
Jun Zhu
Bo Zhang
200
17
0
10 Jun 2019
Quantization-Based Regularization for Autoencoders
Hanwei Wu
M. Flierl
DRL
229
2
0
27 May 2019
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing
Hao Fu
Chunyuan Li
Xiaodong Liu
Jianfeng Gao
Asli Celikyilmaz
Lawrence Carin
ODL
388
426
0
25 Mar 2019
Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering
S. Kamyab
Rasool Sabzi
Z. Azimifar
DRL
148
0
0
11 Mar 2019
Training Variational Autoencoders with Buffered Stochastic Variational Inference
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Rui Shu
Hung Bui
Jay Whang
Stefano Ermon
BDL
184
3
0
27 Feb 2019
Gaussian Mean Field Regularizes by Limiting Learned Information
Entropy (Entropy), 2019
Julius Kunze
Louis Kirsch
H. Ritter
David Barber
FedML
MLT
193
2
0
12 Feb 2019
Meta-Amortized Variational Inference and Learning
Mike Wu
Kristy Choi
Noah D. Goodman
Stefano Ermon
OOD
VLM
BDL
DRL
250
39
0
05 Feb 2019
Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization
Aditya Grover
Stefano Ermon
324
55
0
26 Dec 2018
Can VAEs Generate Novel Examples?
Alican Bozkurt
Babak Esmaeili
Dana H. Brooks
Jennifer G. Dy
Jan-Willem van de Meent
VLM
DRL
184
5
0
22 Dec 2018
Neural Joint Source-Channel Coding
Kristy Choi
Kedar Tatwawadi
Aditya Grover
Tsachy Weissman
Stefano Ermon
378
40
0
19 Nov 2018
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