Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1912.03263
Cited By
v1
v2
v3 (latest)
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
International Conference on Learning Representations (ICLR), 2019
6 December 2019
Will Grathwohl
Kuan-Chieh Wang
J. Jacobsen
David Duvenaud
Mohammad Norouzi
Kevin Swersky
VLM
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One"
40 / 390 papers shown
A Neural Network MCMC sampler that maximizes Proposal Entropy
Zengyi Li
Yubei Chen
Friedrich T. Sommer
260
15
0
07 Oct 2020
Conditional Generative Modeling via Learning the Latent Space
Sameera Ramasinghe
Kanchana Ranasinghe
Salman Khan
Nick Barnes
Stephen Gould
BDL
206
9
0
07 Oct 2020
Generative Model-Enhanced Human Motion Prediction
Applied AI Letters (AA), 2020
Anthony Bourached
Ryan-Rhys Griffiths
Robert J. Gray
A. Jha
P. Nachev
233
15
0
05 Oct 2020
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
International Conference on Learning Representations (ICLR), 2020
Zhisheng Xiao
Karsten Kreis
Jan Kautz
Arash Vahdat
424
136
0
01 Oct 2020
Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of Generative Model
IEEE Transactions on Radiation and Plasma Medical Sciences (TRPMS), 2020
Zhuonan He
Yikun Zhang
Yu Guan
S. Niu
Yi Zhang
Yang Chen
Qiegen Liu
DiffM
MedIm
216
14
0
27 Sep 2020
A Unifying Review of Deep and Shallow Anomaly Detection
Proceedings of the IEEE (Proc. IEEE), 2020
Lukas Ruff
Jacob R. Kauffmann
Robert A. Vandermeulen
G. Montavon
Wojciech Samek
Matthias Kirchler
Thomas G. Dietterich
Klaus-Robert Muller
UQCV
572
929
0
24 Sep 2020
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings
John Mitros
A. Pakrashi
Brian Mac Namee
UQCV
304
2
0
03 Sep 2020
Likelihood Landscapes: A Unifying Principle Behind Many Adversarial Defenses
Fu-Huei Lin
Rohit Mittapalli
Prithvijit Chattopadhyay
Daniel Bolya
Judy Hoffman
AAML
156
2
0
25 Aug 2020
Generative Classifiers as a Basis for Trustworthy Image Classification
Radek Mackowiak
Lynton Ardizzone
Ullrich Kothe
Carsten Rother
208
4
0
29 Jul 2020
Hybrid Discriminative-Generative Training via Contrastive Learning
Hao Liu
Pieter Abbeel
SSL
188
42
0
17 Jul 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
Neural Information Processing Systems (NeurIPS), 2020
Jihoon Tack
Sangwoo Mo
Jongheon Jeong
Jinwoo Shin
OODD
305
677
0
16 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching
Tianyu Pang
Kun Xu
Chongxuan Li
Yang Song
Stefano Ermon
Jun Zhu
DiffM
288
62
0
07 Jul 2020
Kernel Stein Generative Modeling
Wei-Cheng Chang
Chun-Liang Li
Youssef Mroueh
Yiming Yang
DiffM
BDL
212
5
0
06 Jul 2020
Supermasks in Superposition
Mitchell Wortsman
Vivek Ramanujan
Rosanne Liu
Aniruddha Kembhavi
Mohammad Rastegari
J. Yosinski
Ali Farhadi
SSL
CLL
522
329
0
26 Jun 2020
Strictly Batch Imitation Learning by Energy-based Distribution Matching
Neural Information Processing Systems (NeurIPS), 2020
Daniel Jarrett
Ioana Bica
M. Schaar
OffRL
191
70
0
25 Jun 2020
Telescoping Density-Ratio Estimation
Benjamin Rhodes
Kai Xu
Michael U. Gutmann
344
122
0
22 Jun 2020
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
4.9K
25,697
0
19 Jun 2020
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features
R. Schirrmeister
Yuxuan Zhou
T. Ball
Dan Zhang
UQCV
384
93
0
18 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
UQCV
UD
EDL
BDL
390
211
0
16 Jun 2020
Rethinking the Role of Gradient-Based Attribution Methods for Model Interpretability
Suraj Srinivas
François Fleuret
FAtt
91
2
0
16 Jun 2020
Exponential Tilting of Generative Models: Improving Sample Quality by Training and Sampling from Latent Energy
Zhisheng Xiao
Qing Yan
Y. Amit
DRL
142
8
0
15 Jun 2020
Revisiting Explicit Regularization in Neural Networks for Well-Calibrated Predictive Uncertainty
Taejong Joo
U. Chung
BDL
UQCV
250
0
0
11 Jun 2020
EDropout: Energy-Based Dropout and Pruning of Deep Neural Networks
Hojjat Salehinejad
S. Valaee
229
52
0
07 Jun 2020
A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning
Interspeech (Interspeech), 2020
Sameer Khurana
Antoine Laurent
Wei-Ning Hsu
J. Chorowski
A. Lancucki
R. Marxer
James R. Glass
SSL
BDL
175
29
0
03 Jun 2020
Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models
International Conference on Learning Representations (ICLR), 2020
Mitch Hill
Jonathan Mitchell
Song-Chun Zhu
AAML
235
86
0
27 May 2020
Lifted Regression/Reconstruction Networks
R. Høier
Christopher Zach
92
8
0
07 May 2020
How to Train Your Energy-Based Model for Regression
British Machine Vision Conference (BMVC), 2020
Fredrik K. Gustafsson
Martin Danelljan
Radu Timofte
Thomas B. Schon
298
44
0
04 May 2020
Protecting Classifiers From Attacks
Statistical Science (Statist. Sci.), 2020
Víctor Gallego
Roi Naveiro
A. Redondo
D. Insua
Fabrizio Ruggeri
AAML
197
2
0
18 Apr 2020
Compositional Visual Generation and Inference with Energy Based Models
Yilun Du
Shuang Li
Igor Mordatch
CoGe
221
25
0
13 Apr 2020
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator
Yuxuan Song
Qiwei Ye
Minkai Xu
Tie-Yan Liu
134
8
0
05 Apr 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability
European Conference on Computer Vision (ECCV), 2020
Maximilian Augustin
Alexander Meinke
Matthias Hein
OOD
318
108
0
20 Mar 2020
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
Neural Information Processing Systems (NeurIPS), 2020
Tong Che
Ruixiang Zhang
Jascha Narain Sohl-Dickstein
Hugo Larochelle
Liam Paull
Yuan Cao
Yoshua Bengio
DiffM
DRL
362
121
0
12 Mar 2020
Generalized Energy Based Models
International Conference on Learning Representations (ICLR), 2020
Michael Arbel
Liang Zhou
Arthur Gretton
DRL
476
91
0
10 Mar 2020
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Neural Information Processing Systems (NeurIPS), 2020
Zhisheng Xiao
Qing Yan
Y. Amit
OODD
384
212
0
06 Mar 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
International Conference on Machine Learning (ICML), 2020
Francesco Croce
Matthias Hein
AAML
624
2,169
0
03 Mar 2020
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
International Conference on Machine Learning (ICML), 2020
Will Grathwohl
Kuan-Chieh Wang
J. Jacobsen
David Duvenaud
R. Zemel
233
14
0
13 Feb 2020
Generative Modeling with Denoising Auto-Encoders and Langevin Sampling
Adam Block
Youssef Mroueh
Alexander Rakhlin
DiffM
572
118
0
31 Jan 2020
Overcoming Catastrophic Forgetting by Generative Regularization
International Conference on Machine Learning (ICML), 2019
Peiqiu Chen
Wei Wei
Cho-Jui Hsieh
Bo Dai
CLL
116
17
0
03 Dec 2019
Flow Contrastive Estimation of Energy-Based Models
Computer Vision and Pattern Recognition (CVPR), 2019
Ruiqi Gao
Erik Nijkamp
Diederik P. Kingma
Zhen Xu
Andrew M. Dai
Ying Nian Wu
GAN
373
121
0
02 Dec 2019
Controversial stimuli: pitting neural networks against each other as models of human recognition
Tal Golan
Prashant C. Raju
N. Kriegeskorte
AAML
219
39
0
21 Nov 2019
Previous
1
2
3
4
5
6
7
8
