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1912.03263
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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
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Papers citing
"Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One"
50 / 390 papers shown
Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization
Computer Vision and Pattern Recognition (CVPR), 2021
Daiqing Li
Junlin Yang
Karsten Kreis
Antonio Torralba
Sanja Fidler
GAN
MedIm
314
216
0
12 Apr 2021
OpenGAN: Open-Set Recognition via Open Data Generation
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Shu Kong
Deva Ramanan
421
263
0
07 Apr 2021
Elsa: Energy-based learning for semi-supervised anomaly detection
British Machine Vision Conference (BMVC), 2021
Sungwon Han
Hyeonho Song
Seungeon Lee
Sungwon Park
M. Cha
210
14
0
29 Mar 2021
Synthesize-It-Classifier: Learning a Generative Classifier through RecurrentSelf-analysis
Computer Vision and Pattern Recognition (CVPR), 2021
Arghya Pal
Raphaël C.-W. Phan
Koksheik Wong
DiffM
130
3
0
26 Mar 2021
Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Lisa Schut
Oscar Key
R. McGrath
Luca Costabello
Bogdan Sacaleanu
Medb Corcoran
Y. Gal
CML
237
51
0
16 Mar 2021
Deep Consensus Learning
Wei Sun
Tianfu Wu
192
2
0
15 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
724
627
0
08 Mar 2021
RNA Alternative Splicing Prediction with Discrete Compositional Energy Network
ACM Conference on Health, Inference, and Learning (CHIL), 2021
Alvin Chan
A. Korsakova
Yew-Soon Ong
F. Winnerdy
K. W. Lim
A. Phan
CoGe
111
2
0
07 Mar 2021
Energy-Based Learning for Scene Graph Generation
Computer Vision and Pattern Recognition (CVPR), 2021
M. Suhail
Abhay Mittal
Behjat Siddiquie
Chris Broaddus
J. Eledath
Gérard Medioni
Leonid Sigal
240
179
0
03 Mar 2021
Counterfactual Zero-Shot and Open-Set Visual Recognition
Computer Vision and Pattern Recognition (CVPR), 2021
Zhongqi Yue
Tan Wang
Hanwang Zhang
Qianru Sun
Xiansheng Hua
BDL
426
226
0
01 Mar 2021
Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning
IEEE International Conference on Robotics and Automation (ICRA), 2021
David S. W. Williams
Matthew Gadd
D. Martini
Paul Newman
OODD
140
15
0
01 Mar 2021
PredDiff: Explanations and Interactions from Conditional Expectations
Artificial Intelligence (AI), 2021
Stefan Blücher
Johanna Vielhaben
Nils Strodthoff
FAtt
300
22
0
26 Feb 2021
A Framework For Pruning Deep Neural Networks Using Energy-Based Models
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021
Hojjat Salehinejad
S. Valaee
CVBM
124
2
0
25 Feb 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses
Neural Information Processing Systems (NeurIPS), 2021
Chengyuan Yao
Pavol Bielik
Petar Tsankov
Martin Vechev
AAML
236
28
0
23 Feb 2021
Domain Impression: A Source Data Free Domain Adaptation Method
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021
V. Kurmi
Venkatesh Subramanian
Vinay P. Namboodiri
TTA
318
173
0
17 Feb 2021
Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine
IEEE International Joint Conference on Neural Network (IJCNN), 2021
F. Tonin
Arun Pandey
Panagiotis Patrinos
Johan A. K. Suykens
OODD
191
14
0
16 Feb 2021
Explaining Neural Scaling Laws
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2021
Yasaman Bahri
Ethan Dyer
Jared Kaplan
Jaehoon Lee
Utkarsh Sharma
341
379
0
12 Feb 2021
Scalable Bayesian Inverse Reinforcement Learning
International Conference on Learning Representations (ICLR), 2021
Alex J. Chan
M. Schaar
OffRL
BDL
293
80
0
12 Feb 2021
Graph Energy-based Model for Substructure Preserving Molecular Design
Ryuichiro Hataya
Hideki Nakayama
Kazuki Yoshizoe
181
6
0
09 Feb 2021
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
International Conference on Machine Learning (ICML), 2021
Will Grathwohl
Kevin Swersky
Milad Hashemi
David Duvenaud
Chris J. Maddison
BDL
297
106
0
08 Feb 2021
Interpretable Neural Networks based classifiers for categorical inputs
S. Zamuner
P. Rios
FAtt
MILM
69
8
0
05 Feb 2021
Dense outlier detection and open-set recognition based on training with noisy negative images
Image and Vision Computing (IVC), 2021
Petra Bevandić
Ivan Kreso
Marin Orsic
Sinisa Segvic
192
31
0
22 Jan 2021
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models
Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2021
Tianxing He
Bryan McCann
Caiming Xiong
Ehsan Hosseini-Asl
145
25
0
18 Jan 2021
How to Train Your Energy-Based Models
Yang Song
Diederik P. Kingma
DiffM
364
304
0
09 Jan 2021
Unobtrusive Pain Monitoring in Older Adults with Dementia using Pairwise and Contrastive Training
IEEE journal of biomedical and health informatics (JBHI), 2020
S. Rezaei
Abhishek Moturu
Shun Zhao
K. Prkachin
T. Hadjistavropoulos
Babak Taati
95
23
0
08 Jan 2021
Energy-constrained Self-training for Unsupervised Domain Adaptation
International Conference on Pattern Recognition (ICPR), 2021
Xiaofeng Liu
Bo Hu
Xiongchang Liu
Jun Lu
J. You
Lingsheng Kong
339
32
0
01 Jan 2021
Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler
AAAI Conference on Artificial Intelligence (AAAI), 2020
Jianwen Xie
Zilong Zheng
Ping Li
265
56
0
29 Dec 2020
Computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation
Bioimaging (Bristol. Print) (BBP), 2020
A. Dubey
M. T. Young
Christopher Stanley
D. Lunga
Jacob D. Hinkle
OOD
194
5
0
19 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers
Jonathan W. Helland
Nathan M. VanHoudnos
AAML
157
4
0
18 Dec 2020
Learning from the Best: Rationalizing Prediction by Adversarial Information Calibration
AAAI Conference on Artificial Intelligence (AAAI), 2020
Lei Sha
Oana-Maria Camburu
Thomas Lukasiewicz
395
40
0
16 Dec 2020
Learning Energy-Based Models by Diffusion Recovery Likelihood
International Conference on Learning Representations (ICLR), 2020
Ruiqi Gao
Yang Song
Ben Poole
Ying Nian Wu
Diederik P. Kingma
DiffM
337
137
0
15 Dec 2020
Learning Energy-Based Models With Adversarial Training
European Conference on Computer Vision (ECCV), 2020
Xuwang Yin
Shiying Li
Gustavo K. Rohde
AAML
DiffM
412
11
0
11 Dec 2020
Composite Adversarial Attacks
AAAI Conference on Artificial Intelligence (AAAI), 2020
Xiaofeng Mao
YueFeng Chen
Shuhui Wang
Hang Su
Yuan He
Hui Xue
AAML
175
58
0
10 Dec 2020
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Dennis Ulmer
Giovanni Cina
OODD
605
35
0
09 Dec 2020
Accurate 3D Object Detection using Energy-Based Models
Fredrik K. Gustafsson
Martin Danelljan
Thomas B. Schon
3DPC
304
11
0
08 Dec 2020
Deep Energy-Based NARX Models
J. Hendriks
Fredrik K. Gustafsson
Antônio H. Ribeiro
A. Wills
Thomas B. Schon
122
11
0
08 Dec 2020
Perfect density models cannot guarantee anomaly detection
Charline Le Lan
Laurent Dinh
418
55
0
07 Dec 2020
Contrastive Divergence Learning is a Time Reversal Adversarial Game
International Conference on Learning Representations (ICLR), 2020
Omer Yair
T. Michaeli
GAN
405
8
0
06 Dec 2020
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization
AAAI Conference on Artificial Intelligence (AAAI), 2020
Kien Do
T. Tran
Svetha Venkatesh
BDL
212
5
0
03 Dec 2020
Improved Contrastive Divergence Training of Energy Based Models
International Conference on Machine Learning (ICML), 2020
Yilun Du
Shuang Li
J. Tenenbaum
Igor Mordatch
642
164
0
02 Dec 2020
Energy-Based Models for Continual Learning
Shuang Li
Yilun Du
Gido M. van de Ven
Igor Mordatch
259
46
0
24 Nov 2020
Dense open-set recognition with synthetic outliers generated by Real NVP
VISIGRAPP (VISIGRAPP), 2020
Matej Grcić
Petra Bevandić
Sinisa Segvic
345
44
0
22 Nov 2020
Multiscale Score Matching for Out-of-Distribution Detection
International Conference on Learning Representations (ICLR), 2020
Ahsan Mahmood
Junier Oliva
M. Styner
OODD
359
33
0
25 Oct 2020
Further Analysis of Outlier Detection with Deep Generative Models
Neural Information Processing Systems (NeurIPS), 2020
Ziyu Wang
Bin Dai
David Wipf
Jun Zhu
222
41
0
25 Oct 2020
Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling
Bo Pang
Erik Nijkamp
Jiali Cui
Tian Han
Ying Nian Wu
SSL
145
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19 Oct 2020
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
International Conference on Machine Learning (ICML), 2020
Fan Bao
Kun Xu
Chongxuan Li
Lanqing Hong
Jun Zhu
Bo Zhang
DiffM
223
10
0
16 Oct 2020
Bi-level Score Matching for Learning Energy-based Latent Variable Models
Fan Bao
Chongxuan Li
Kun Xu
Hang Su
Jun Zhu
Bo Zhang
183
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15 Oct 2020
No MCMC for me: Amortized sampling for fast and stable training of energy-based models
International Conference on Learning Representations (ICLR), 2020
Will Grathwohl
Jacob Kelly
Milad Hashemi
Mohammad Norouzi
Kevin Swersky
David Duvenaud
346
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08 Oct 2020
Set Prediction without Imposing Structure as Conditional Density Estimation
International Conference on Learning Representations (ICLR), 2020
David W. Zhang
Gertjan J. Burghouts
Cees G. M. Snoek
215
18
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08 Oct 2020
Energy-based Out-of-distribution Detection
Weitang Liu
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OODD
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