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Sliced Score Matching: A Scalable Approach to Density and Score
  Estimation
v1v2 (latest)

Sliced Score Matching: A Scalable Approach to Density and Score Estimation

Conference on Uncertainty in Artificial Intelligence (UAI), 2019
17 May 2019
Yang Song
Sahaj Garg
Jiaxin Shi
Stefano Ermon
ArXiv (abs)PDFHTML

Papers citing "Sliced Score Matching: A Scalable Approach to Density and Score Estimation"

50 / 333 papers shown
MARS: Meta-Learning as Score Matching in the Function Space
MARS: Meta-Learning as Score Matching in the Function SpaceInternational Conference on Learning Representations (ICLR), 2022
Krunoslav Lehman Pavasovic
Jonas Rothfuss
Andreas Krause
BDL
388
7
0
24 Oct 2022
Improving Adversarial Robustness by Contrastive Guided Diffusion Process
Improving Adversarial Robustness by Contrastive Guided Diffusion ProcessInternational Conference on Machine Learning (ICML), 2022
Yidong Ouyang
Liyan Xie
Guang Cheng
198
10
0
18 Oct 2022
Action Matching: Learning Stochastic Dynamics from Samples
Action Matching: Learning Stochastic Dynamics from SamplesInternational Conference on Machine Learning (ICML), 2022
Kirill Neklyudov
Rob Brekelmans
Daniel de Souza Severo
Alireza Makhzani
365
76
0
13 Oct 2022
Diffusion Models for Causal Discovery via Topological Ordering
Diffusion Models for Causal Discovery via Topological OrderingInternational Conference on Learning Representations (ICLR), 2022
Pedro Sanchez
Xiao Liu
Alison Q. OÑeil
Sotirios A. Tsaftaris
DiffM
417
63
0
12 Oct 2022
Gradient-Guided Importance Sampling for Learning Binary Energy-Based
  Models
Gradient-Guided Importance Sampling for Learning Binary Energy-Based ModelsInternational Conference on Learning Representations (ICLR), 2022
Meng Liu
Haoran Liu
Shuiwang Ji
217
6
0
11 Oct 2022
Sequential Neural Score Estimation: Likelihood-Free Inference with
  Conditional Score Based Diffusion Models
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion ModelsInternational Conference on Machine Learning (ICML), 2022
Louis Sharrock
J. Simons
Song Liu
Mark Beaumont
DiffM
287
50
0
10 Oct 2022
FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the
  Underlying Score Fokker-Planck Equation
FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the Underlying Score Fokker-Planck EquationInternational Conference on Machine Learning (ICML), 2022
Chieh-Hsin Lai
Yuhta Takida
Naoki Murata
Toshimitsu Uesaka
Yuki Mitsufuji
Stefano Ermon
DiffM
262
38
0
09 Oct 2022
Towards Understanding and Boosting Adversarial Transferability from a
  Distribution Perspective
Towards Understanding and Boosting Adversarial Transferability from a Distribution PerspectiveIEEE Transactions on Image Processing (IEEE TIP), 2022
Yao Zhu
YueFeng Chen
Xiaodan Li
Kejiang Chen
Yuan He
Xiang Tian
Bo Zheng
Yao-wu Chen
Qingming Huang
AAML
168
69
0
09 Oct 2022
Statistical Efficiency of Score Matching: The View from Isoperimetry
Statistical Efficiency of Score Matching: The View from IsoperimetryInternational Conference on Learning Representations (ICLR), 2022
Frederic Koehler
Alexander Heckett
Andrej Risteski
DiffM
321
60
0
03 Oct 2022
Hierarchical Sliced Wasserstein Distance
Hierarchical Sliced Wasserstein DistanceInternational Conference on Learning Representations (ICLR), 2022
Khai Nguyen
Zhaolin Ren
Huy Nguyen
Litu Rout
T. Nguyen
Nhat Ho
309
27
0
27 Sep 2022
On Investigating the Conservative Property of Score-Based Generative
  Models
On Investigating the Conservative Property of Score-Based Generative ModelsInternational Conference on Machine Learning (ICML), 2022
Chen-Hao Chao
Wei-Fang Sun
Bo Wun Cheng
Chun-Yi Lee
248
15
0
26 Sep 2022
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian
  Preserving Flows
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows
G. Morel
Lucas Drumetz
Simon Benaïchouche
Nicolas Courty
F. Rousseau
OT
417
6
0
22 Sep 2022
Diffusion Models in Vision: A Survey
Diffusion Models in Vision: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Florinel-Alin Croitoru
Vlad Hondru
Radu Tudor Ionescu
M. Shah
DiffMVLMMedIm
1.2K
1,761
0
10 Sep 2022
Learning to Generate Realistic LiDAR Point Clouds
Learning to Generate Realistic LiDAR Point CloudsEuropean Conference on Computer Vision (ECCV), 2022
Vlas Zyrianov
Xiyue Zhu
Shenlong Wang
3DPCDiffM
386
95
0
08 Sep 2022
A Survey on Generative Diffusion Model
A Survey on Generative Diffusion ModelIEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
Hanqun Cao
Cheng Tan
Zhangyang Gao
Yilun Xu
Guangyong Chen
Pheng-Ann Heng
Stan Z. Li
MedIm
765
411
0
06 Sep 2022
Unifying Generative Models with GFlowNets and Beyond
Unifying Generative Models with GFlowNets and Beyond
Dinghuai Zhang
Ricky T. Q. Chen
Nikolay Malkin
Yoshua Bengio
BDLAI4CE
262
26
0
06 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
Diffusion Models: A Comprehensive Survey of Methods and ApplicationsACM Computing Surveys (ACM CSUR), 2022
Ling Yang
Zhilong Zhang
Yingxia Shao
Shenda Hong
Runsheng Xu
Yue Zhao
Wentao Zhang
Tengjiao Wang
Ming-Hsuan Yang
DiffMMedIm
1.5K
1,882
0
02 Sep 2022
Understanding Diffusion Models: A Unified Perspective
Understanding Diffusion Models: A Unified Perspective
Calvin Luo
DiffM
295
463
0
25 Aug 2022
Semantic Driven Energy based Out-of-Distribution Detection
Semantic Driven Energy based Out-of-Distribution DetectionIEEE International Joint Conference on Neural Network (IJCNN), 2022
Abhishek Joshi
Sathish Chalasani
K. N. Iyer
OODD
133
4
0
23 Aug 2022
Classification via score-based generative modelling
Classification via score-based generative modelling
Yongchao Huang
DiffM
113
2
0
22 Jul 2022
Generative Adversarial Networks and Other Generative Models
Generative Adversarial Networks and Other Generative Models
Markus T. Wenzel
GAN
166
16
0
08 Jul 2022
A Flexible Diffusion Model
A Flexible Diffusion ModelInternational Conference on Machine Learning (ICML), 2022
Weitao Du
Tao Yang
Heidi Zhang
Yuanqi Du
DiffM
186
12
0
17 Jun 2022
Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order
  Denoising Score Matching
Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score MatchingInternational Conference on Machine Learning (ICML), 2022
Cheng Lu
Kaiwen Zheng
Fan Bao
Jianfei Chen
Chongxuan Li
Jun Zhu
DiffM
262
101
0
16 Jun 2022
Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of
  Normalizing Flows
Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing FlowsInternational Conference on Machine Learning (ICML), 2022
Phillip Si
Zeyi Chen
Subham S. Sahoo
Yair Schiff
Volodymyr Kuleshov
234
9
0
14 Jun 2022
Convergence for score-based generative modeling with polynomial
  complexity
Convergence for score-based generative modeling with polynomial complexityNeural Information Processing Systems (NeurIPS), 2022
Holden Lee
Jianfeng Lu
Yixin Tan
DiffM
237
172
0
13 Jun 2022
Score-Based Generative Models Detect Manifolds
Score-Based Generative Models Detect ManifoldsNeural Information Processing Systems (NeurIPS), 2022
Jakiw Pidstrigach
DiffM
453
110
0
02 Jun 2022
A Kernelised Stein Statistic for Assessing Implicit Generative Models
A Kernelised Stein Statistic for Assessing Implicit Generative ModelsNeural Information Processing Systems (NeurIPS), 2022
Wenkai Xu
Gesine Reinert
SyDa
232
4
0
31 May 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models
Maximum Likelihood Training of Implicit Nonlinear Diffusion ModelsNeural Information Processing Systems (NeurIPS), 2022
Dongjun Kim
Byeonghu Na
S. Kwon
Dongsoo Lee
Wanmo Kang
Il-Chul Moon
DiffM
660
59
0
27 May 2022
HessianFR: An Efficient Hessian-based Follow-the-Ridge Algorithm for
  Minimax Optimization
HessianFR: An Efficient Hessian-based Follow-the-Ridge Algorithm for Minimax Optimization
Yihang Gao
Huafeng Liu
Michael K. Ng
Mingjie Zhou
150
3
0
23 May 2022
Statistical applications of contrastive learning
Statistical applications of contrastive learning
Michael U. Gutmann
Steven Kleinegesse
Benjamin Rhodes
196
9
0
29 Apr 2022
DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations
DiffMD: A Geometric Diffusion Model for Molecular Dynamics SimulationsAAAI Conference on Artificial Intelligence (AAAI), 2022
Fang Wu
Stan Z. Li
DiffM
229
41
0
19 Apr 2022
Denoising Likelihood Score Matching for Conditional Score-based Data
  Generation
Denoising Likelihood Score Matching for Conditional Score-based Data GenerationInternational Conference on Learning Representations (ICLR), 2022
Chen-Hao Chao
Wei-Fang Sun
Bo Wun Cheng
Yi-Chen Lo
Chia-Che Chang
Yu-Lun Liu
Yu-Lin Chang
Chia-Ping Chen
Chun-Yi Lee
DiffM
189
51
0
27 Mar 2022
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality
  Speech Synthesis
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech SynthesisInternational Conference on Learning Representations (ICLR), 2022
Max W. Y. Lam
Jun Wang
Jane Polak Scowcroft
Dong Yu
DiffM
218
104
0
25 Mar 2022
Generalized Score Matching for Regression
Generalized Score Matching for Regression
Jiazhen Xu
J. Scealy
A. Wood
Tao Zou
129
6
0
18 Mar 2022
Score matching enables causal discovery of nonlinear additive noise
  models
Score matching enables causal discovery of nonlinear additive noise modelsInternational Conference on Machine Learning (ICML), 2022
Paul Rolland
Volkan Cevher
Matthäus Kleindessner
Chris Russel
Bernhard Schölkopf
Dominik Janzing
Francesco Locatello
CML
292
112
0
08 Mar 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Robustness and Accuracy Could Be Reconcilable by (Proper) DefinitionInternational Conference on Machine Learning (ICML), 2022
Tianyu Pang
Min Lin
Xiao Yang
Junyi Zhu
Shuicheng Yan
403
150
0
21 Feb 2022
A Differential Entropy Estimator for Training Neural Networks
A Differential Entropy Estimator for Training Neural NetworksInternational Conference on Machine Learning (ICML), 2022
Georg Pichler
Pierre Colombo
Malik Boudiaf
Günther Koliander
Pablo Piantanida
297
26
0
14 Feb 2022
Heavy-tailed denoising score matching
Heavy-tailed denoising score matching
J. Deasy
Nikola Simidjievski
Pietro Lio
DiffM
226
20
0
17 Dec 2021
Density Ratio Estimation via Infinitesimal Classification
Density Ratio Estimation via Infinitesimal ClassificationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Kristy Choi
Chenlin Meng
Yang Song
Stefano Ermon
363
54
0
22 Nov 2021
Estimating High Order Gradients of the Data Distribution by Denoising
Estimating High Order Gradients of the Data Distribution by Denoising
Chenlin Meng
Yang Song
Wenzhe Li
Stefano Ermon
DiffM
212
62
0
08 Nov 2021
Pseudo-Spherical Contrastive Divergence
Pseudo-Spherical Contrastive DivergenceNeural Information Processing Systems (NeurIPS), 2021
Lantao Yu
Jiaming Song
Yang Song
Stefano Ermon
221
7
0
01 Nov 2021
Score-based diffusion models for accelerated MRI
Score-based diffusion models for accelerated MRI
Hyungjin Chung
Jong Chul Ye
DiffMMedIm
500
501
0
08 Oct 2021
Smooth Normalizing Flows
Smooth Normalizing Flows
Jonas Köhler
Andreas Krämer
Frank Noé
336
63
0
01 Oct 2021
Interpreting diffusion score matching using normalizing flow
Interpreting diffusion score matching using normalizing flow
Wenbo Gong
Yingzhen Li
DiffM
186
13
0
21 Jul 2021
On Out-of-distribution Detection with Energy-based Models
On Out-of-distribution Detection with Energy-based Models
Sven Elflein
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
OODD
160
22
0
03 Jul 2021
Conjugate Energy-Based Models
Conjugate Energy-Based ModelsInternational Conference on Machine Learning (ICML), 2021
Hao Wu
Babak Esmaeili
Michael L. Wick
Jean-Baptiste Tristan
Jan-Willem van de Meent
203
2
0
25 Jun 2021
ScoreGrad: Multivariate Probabilistic Time Series Forecasting with
  Continuous Energy-based Generative Models
ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models
Tijin Yan
Hongwei Zhang
Tong Zhou
Yufeng Zhan
Yuanqing Xia
DiffMAI4TS
270
47
0
18 Jun 2021
Score-based Generative Modeling in Latent Space
Score-based Generative Modeling in Latent SpaceNeural Information Processing Systems (NeurIPS), 2021
Arash Vahdat
Karsten Kreis
Jan Kautz
DiffM
430
801
0
10 Jun 2021
Learning to Efficiently Sample from Diffusion Probabilistic Models
Learning to Efficiently Sample from Diffusion Probabilistic Models
Daniel Watson
Jonathan Ho
Mohammad Norouzi
William Chan
DiffM
320
151
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Meta-Learning Reliable Priors in the Function Space
Meta-Learning Reliable Priors in the Function SpaceNeural Information Processing Systems (NeurIPS), 2021
Jonas Rothfuss
Dominique Heyn
Jinfan Chen
Andreas Krause
260
29
0
06 Jun 2021
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