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

Conference on Uncertainty in Artificial Intelligence (UAI), 2019

17 May 2019

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

50 / 333 papers shown

Title
Provable Statistical Rates for Consistency Diffusion Models Zehao Dou Minshuo Chen Mengdi Wang Zhuoran Yang DiffM 258 3 0 23 Jun 2024
Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow Zhichao Chen Haoxuan Li Fangyikang Wang Odin Zhang Hu Xu Xiaoyu Jiang Zhihuan Song Eric H. Wang DiffM 181 4 0 22 Jun 2024
Neural Residual Diffusion Models for Deep Scalable Vision GenerationNeural Information Processing Systems (NeurIPS), 2024 Zhiyuan Ma Liangliang Zhao Biqing Qi Bowen Zhou DiffM 389 7 0 19 Jun 2024
Variational Distillation of Diffusion Policies into Mixture of ExpertsNeural Information Processing Systems (NeurIPS), 2024 Hongyi Zhou Denis Blessing Ge Li Onur Celik Xiaogang Jia Gerhard Neumann Rudolf Lioutikov DiffM 236 7 0 18 Jun 2024
Score-fPINN: Fractional Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck-Levy Equations Zheyuan Hu Zhongqiang Zhang George Karniadakis Kenji Kawaguchi 166 2 0 17 Jun 2024
Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and Transparency Maor Dikter Tsachi Blau Chaim Baskin 283 0 0 13 Jun 2024
Operator-Informed Score Matching for Markov Diffusion Models Zheyang Shen Huihui Wang Marina Riabiz Chris J. Oates DiffM 376 0 0 13 Jun 2024
Linear Causal Representation Learning from Unknown Multi-node InterventionsNeural Information Processing Systems (NeurIPS), 2024 Burak Varıcı Emre Acartürk Karthikeyan Shanmugam A. Tajer CML 183 5 0 09 Jun 2024
$Diffusion Models in $\textit{De Novo}$ Drug Design$ Diffusion Models in $\textit{De Novo}$ Drug DesignJournal of Chemical Information and Modeling (JCIM), 2024 Amira Alakhdar Barnabas Poczos Newell Washburn MedIm 175 54 0 07 Jun 2024
On the Hardness of Sampling from Mixture Distributions via Langevin Dynamics Xiwei Cheng Kexin Fu Farzan Farnia 451 0 0 04 Jun 2024
Sifting through the Noise: A Survey of Diffusion Probabilistic Models and Their Applications to Biomolecules Trevor Norton Debswapna Bhattacharya MedIm DiffM 221 2 0 31 May 2024
Kernel Semi-Implicit Variational Inference Ziheng Cheng Longlin Yu Tianyu Xie Shiyue Zhang Cheng Zhang 229 7 0 29 May 2024
Transfer Learning for Diffusion Models Yidong Ouyang Liyan Xie Hongyuan Zha Guang Cheng DiffM 260 7 0 27 May 2024
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups Yuchen Zhu Tianrong Chen Lingkai Kong Evangelos A. Theodorou Molei Tao DiffM 261 13 0 25 May 2024
Score-based generative models are provably robust: an uncertainty quantification perspective Nikiforos Mimikos-Stamatopoulos Benjamin J. Zhang Markos A. Katsoulakis DiffM 232 11 0 24 May 2024
Model Free Prediction with Uncertainty Assessment Yuling Jiao Lican Kang Jin Liu Heng Peng Heng Zuo DiffM 317 2 0 21 May 2024
Distilling Diffusion Models into Conditional GANsEuropean Conference on Computer Vision (ECCV), 2024 Minguk Kang Richard Zhang Connelly Barnes Sylvain Paris Suha Kwak Jaesik Park Eli Shechtman Jun-Yan Zhu Taesung Park 746 72 0 09 May 2024
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations Kaiwen Xue Yuhao Zhou Shen Nie Xu Min Xiaolu Zhang Jun Zhou Chongxuan Li DiffM 261 21 0 24 Apr 2024
Gradient Guidance for Diffusion Models: An Optimization Perspective Yingqing Guo Hui Yuan Yukang Yang Minshuo Chen Mengdi Wang 253 45 0 23 Apr 2024
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization Minshuo Chen Song Mei Jianqing Fan Mengdi Wang VLM MedIm DiffM 276 82 0 11 Apr 2024
Diffusion Model for Data-Driven Black-Box Optimization Zihao Li Hui Yuan Kaixuan Huang Chengzhuo Ni Yinyu Ye Minshuo Chen Mengdi Wang DiffM 231 19 0 20 Mar 2024
Fine-tuning of diffusion models via stochastic control: entropy regularization and beyond Wenpin Tang Fuzhong Zhou 359 27 0 10 Mar 2024
Improving Adversarial Energy-Based Model via Diffusion Process Cong Geng Tian Han Peng-Tao Jiang Hao Zhang Jinwei Chen Søren Hauberg Yue Liu DiffM 422 5 0 04 Mar 2024
Generative AI in Vision: A Survey on Models, Metrics and Applications Gaurav Raut Apoorv Singh VLM MedIm 202 12 0 26 Feb 2024
Generative Modelling with Tensor Train approximations of Hamilton--Jacobi--Bellman equations David Sommer Robert Gruhlke Max Kirstein Martin Eigel Claudia Schillings 132 4 0 23 Feb 2024
Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities Fengyi Li Ayoub Belhadji Youssef Marzouk 119 3 0 23 Feb 2024
Classification Diffusion Models: Revitalizing Density Ratio Estimation Shahar Yadin Noam Elata T. Michaeli DiffM 262 2 0 15 Feb 2024
Optimal score estimation via empirical Bayes smoothing Andre Wibisono Yihong Wu Kaylee Yingxi Yang 262 40 0 12 Feb 2024
Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations Zheyuan Hu Zhongqiang Zhang George Karniadakis Kenji Kawaguchi 197 18 0 12 Feb 2024
Score-based Diffusion Models via Stochastic Differential Equations -- a Technical TutorialStatistics Survey (Stat. Surv.), 2024 Wenpin Tang Hanyang Zhao DiffM 379 41 0 12 Feb 2024
Wasserstein proximal operators describe score-based generative models and resolve memorization Benjamin J. Zhang Siting Liu Wuchen Li Markos A. Katsoulakis Stanley J. Osher DiffM 244 14 0 09 Feb 2024
Stable Autonomous Flow Matching Christopher Iliffe Sprague Arne Elofsson Hossein Azizpour 162 1 0 08 Feb 2024
SDEMG: Score-based Diffusion Model for Surface Electromyographic Signal DenoisingIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024 Yu-Tung Liu Kuan-Chen Wang Kai-Chun Liu Sheng-Yu Peng Yu Tsao DiffM MedIm 190 9 0 06 Feb 2024
Analyzing Neural Network-Based Generative Diffusion Models through Convex Optimization Fangzhao Zhang Mert Pilanci DiffM 304 5 0 03 Feb 2024
Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances Xuefeng Gao Lingjiong Zhu 276 37 0 31 Jan 2024
Contractive Diffusion Probabilistic Models Wenpin Tang Hanyang Zhao DiffM 275 22 0 23 Jan 2024
Building Minimal and Reusable Causal State Abstractions for Reinforcement LearningAAAI Conference on Artificial Intelligence (AAAI), 2024 Zizhao Wang Caroline Wang Xuesu Xiao Yuke Zhu Peter Stone OffRL 125 9 0 23 Jan 2024
The Rise of Diffusion Models in Time-Series Forecasting Caspar Meijer Lydia Y. Chen DiffM AI4TS 250 24 0 05 Jan 2024
From Function to Distribution Modeling: A PAC-Generative Approach to Offline Optimization Qiang Zhang Ruida Zhou Yang Shen Tie Liu OffRL 267 1 0 04 Jan 2024
Diffusion Models, Image Super-Resolution And Everything: A SurveyIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024 Brian B. Moser Arundhati S. Shanbhag Federico Raue Stanislav Frolov Sebastián M. Palacio Andreas Dengel 426 96 0 01 Jan 2024
Taming Mode Collapse in Score Distillation for Text-to-3D GenerationComputer Vision and Pattern Recognition (CVPR), 2023 Peihao Wang Dejia Xu Zhiwen Fan Dilin Wang Sreyas Mohan ... Rakesh Ranjan Yilei Li Qiang Liu Zinan Lin Vikas Chandra DiffM 289 40 0 31 Dec 2023
Investigating the Design Space of Diffusion Models for Speech Enhancement Philippe Gonzalez Zheng-Hua Tan Jan Østergaard Jesper Jensen T. S. Alstrøm Tobias May DiffM 239 19 0 07 Dec 2023
DPHMs: Diffusion Parametric Head Models for Depth-based TrackingComputer Vision and Pattern Recognition (CVPR), 2023 Jiapeng Tang Angela Dai Yinyu Nie Lev Markhasin Justus Thies Matthias Niessner DiffM 533 11 0 02 Dec 2023
DeepCache: Accelerating Diffusion Models for FreeComputer Vision and Pattern Recognition (CVPR), 2023 Xinyin Ma Gongfan Fang Xinchao Wang 406 252 0 01 Dec 2023
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A Survey of Emerging Applications of Diffusion Probabilistic Models in MRI Yuheng Fan Hanxi Liao Shiqi Huang Yimin Luo Huazhu Fu Haikun Qi MedIm 460 30 0 19 Nov 2023
SceneScore: Learning a Cost Function for Object Arrangement Ivan Kapelyukh Edward Johns OffRL DiffM OCL 216 6 0 14 Nov 2023
Variational Weighting for Kernel Density RatiosNeural Information Processing Systems (NeurIPS), 2023 Sangwoong Yoon Frank C. Park Gunsu S Yun Iljung Kim Yung-Kyun Noh 116 0 0 06 Nov 2023
Diffusion Models for Reinforcement Learning: A Survey Zhengbang Zhu Hanye Zhao Haoran He Yichao Zhong Shenyu Zhang Haoquan Guo Tingting Chen Weinan Zhang 571 92 0 02 Nov 2023
Scaling Riemannian Diffusion ModelsNeural Information Processing Systems (NeurIPS), 2023 Aaron Lou Minkai Xu Stefano Ermon 188 12 0 30 Oct 2023

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

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