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Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm

16 August 2016

Papers citing "Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm"

50 / 638 papers shown

Title
Thermodynamic Performance Limits for Score-Based Diffusion Models Nathan X. Kodama Michael Hinczewski DiffM 0 0 0 07 Oct 2025
Adaptive Kernel Selection for Stein Variational Gradient Descent Moritz Melcher Simon Weissmann Ashia C. Wilson Jakob Zech 8 0 0 02 Oct 2025
Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points Naoya Yamamoto Juno Kim Taiji Suzuki 40 0 0 21 Sep 2025
Distribution Estimation for Global Data Association via Approximate Bayesian Inference Yixuan Jia Mason B. Peterson Qingyuan Li Yulun Tian Jonathan P. How 0 0 0 19 Sep 2025
Is the `Agent' Paradigm a Limiting Framework for Next-Generation Intelligent Systems? Jesse Gardner Vladimir A. Baulin LM&Ro 12 0 0 13 Sep 2025
Flow Straight and Fast in Hilbert Space: Functional Rectified Flow Jianxin Zhang Clayton Scott 16 0 0 12 Sep 2025
SVN-ICP: Uncertainty Estimation of ICP-based LiDAR Odometry using Stein Variational Newton Shiping Ma Haoming Zhang Marc Toussaint 28 0 0 09 Sep 2025
Simulation Priors for Data-Efficient Deep Learning Lenart Treven Bhavya Sukhija Jonas Rothfuss Stelian Coros Florian Dorfler Andreas Krause 16 0 0 06 Sep 2025
Towards understanding Accelerated Stein Variational Gradient Flow -- Analysis of Generalized Bilinear Kernels for Gaussian target distributions Viktor Stein Wuchen Li 32 0 0 04 Sep 2025
Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference Yixuan Huang Novella Alvina M. Shanthi Tucker Hermans 40 0 0 01 Sep 2025
MARS: Modality-Aligned Retrieval for Sequence Augmented CTR Prediction Yutian Xiao Shukuan Wang Binhao Wang Zhao Zhang Yanze Zhang Shanqi Liu Chao Feng Xiang Li Fuzhen Zhuang 20 0 0 01 Sep 2025
Are We Really Learning the Score Function? Reinterpreting Diffusion Models Through Wasserstein Gradient Flow Matching An B. Vuong Michael T. McCann Javier E. Santos Yen Ting Lin DiffM 20 1 0 30 Aug 2025
Training-Free Stein Diffusion Guidance: Posterior Correction for Sampling Beyond High-Density Regions Van Khoa Nguyen Lionel Blondé Alexandros Kalousis 44 0 0 07 Jul 2025
FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation Maolin Wang Yutian Xiao Binhao Wang Sheng Zhang Shanshan Ye Wanyu Wang Hongzhi Yin Ruocheng Guo Zenglin Xu 40 0 0 07 Jul 2025
Branching Stein Variational Gradient Descent for sampling multimodal distributions Isaias Banales Arturo Jaramillo Heli Ricalde Guerrero 69 0 0 16 Jun 2025
Variational Inference Optimized Using the Curved Geometry of Coupled Free Energy Kenric Nelson Igor Oliveira Amenah Al-Najafi Fode Zhang Hon Keung Tony Ng DRL 144 1 0 10 Jun 2025
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models Ngoc-Quan Pham Tuan Truong Quyen Tran T. H. Nguyen Dinh Q. Phung T. Le 115 3 0 08 Jun 2025
A Framework for Controllable Multi-objective Learning with Annealed Stein Variational Hypernetworks Minh-Duc Nguyen Dung D. Le 114 0 0 07 Jun 2025
Sequential Monte Carlo approximations of Wasserstein--Fisher--Rao gradient flows Francesca R. Crucinio Sahani Pathiraja 133 1 0 06 Jun 2025
Semi-Implicit Variational Inference via Kernelized Path Gradient Descent Tobias Pielok Bernd Bischl David Rügamer 216 0 0 05 Jun 2025
Constrained Stein Variational Gradient Descent for Robot Perception, Planning, and Identification Griffin Tabor Tucker Hermans 89 1 0 31 May 2025
STACI: Spatio-Temporal Aleatoric Conformal Inference Brandon Feng David K. Park Xihaier Luo Arantxa Urdangarin Shinjae Yoo Brian J. Reich 92 0 0 27 May 2025
Stationary MMD Points for Cubature Zonghao Chen Toni Karvonen Heishiro Kanagawa F. Briol Chris J. Oates 180 0 0 27 May 2025
Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization Dai Hai Nguyen Hiroshi Mamitsuka Atsuyoshi Nakamura 120 0 0 24 May 2025
Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks Philipp Pilar Markus Heinonen Niklas Wahlström PINN 125 0 0 22 May 2025
Nonparametric Teaching for Graph Property Learners Chen Zhang Weixin Bu Zhaochun Ren Ziyue Liu Yik-Chung Wu Ngai Wong 219 0 0 20 May 2025
Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation Ting Wei Biao Mei Junliang Lyu Renquan Zhang Feng Zhou Yifan Sun FedML 107 0 0 20 May 2025
Adaptive Diffusion Constrained Sampling for Bimanual Robot Manipulation Haolei Tong Yuezhe Zhang Sophie Lueth Georgia Chalvatzaki 165 0 0 19 May 2025
Training Latent Diffusion Models with Interacting Particle Algorithms Tim Y. J. Wang Juan Kuntz O. Deniz Akyildiz 237 1 0 18 May 2025
Missing Data Imputation by Reducing Mutual Information with Rectified Flows Jiahao Yu Qizhen Ying Leyang Wang Z. L. Jiang Song Liu 144 0 0 16 May 2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 124 0 0 08 May 2025
Variational Formulation of the Particle Flow Particle Filter Yinzhuang Yi Jorge Cortés Nikolay Atanasov 118 0 0 06 May 2025
Flow Matching Ergodic Coverage Max Muchen Sun Allison Pinosky Todd Murphey 129 0 0 24 Apr 2025
Uncertainty quantification of neural network models of evolving processes via Langevin sampling Cosmin Safta Reese E. Jones Ravi G. Patel Raelynn Wonnacot Dan S. Bolintineanu Craig M. Hamel S. Kramer BDL 234 2 0 21 Apr 2025
Visual Prompting for One-shot Controllable Video Editing without Inversion Zitao Gao Yuxi Zhou Duo Peng Joo-Hwee Lim Zhigang Tu De Wen Soh Lin Geng Foo DiffM 153 2 0 19 Apr 2025
DiverseFlow: Sample-Efficient Diverse Mode Coverage in Flows Mashrur M. Morshed Vishnu Boddeti 169 0 0 10 Apr 2025
Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference Jiayun Li Kay Pompetzki An T. Le Haolei Tong Jan Peters Georgia Chalvatzaki 134 0 0 07 Apr 2025
Taming High-Dimensional Dynamics: Learning Optimal Projections onto Spectral Submanifolds Hugo Buurmeijer Luis A. Pabon J. I. Alora Roshan S. Kaundinya George Haller Marco Pavone 161 0 0 04 Apr 2025
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification Jonas Teufel Annika Leinweber Pascal Friederich 215 3 0 03 Apr 2025
Accelerated Stein Variational Gradient Flow Viktor Stein Wuchen Li 161 1 0 30 Mar 2025
Low Stein Discrepancy via Message-Passing Monte Carlo Nathan Kirk T. Konstantin Rusch Jakob Zech Daniela Rus 97 3 0 27 Mar 2025
Offline Model-Based Optimization: Comprehensive Review Minsu Kim Jiayao Gu Ye Yuan Taeyoung Yun Ziqiang Liu Yoshua Bengio Can Chen OffRL 183 8 0 21 Mar 2025
Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization Chandan Tankala Dheeraj M. Nagaraj Anant Raj 95 1 0 17 Mar 2025
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference Jasmeet Kaur BDL UQCV 240 0 0 15 Mar 2025
RayFlow: Instance-Aware Diffusion Acceleration via Adaptive Flow Trajectories Huiyang Shao Xin Xia Yanting Yang Yuxi Ren Xing Wang Xuefeng Xiao 149 7 0 10 Mar 2025
Efficient Gradient-Based Inference for Manipulation Planning in Contact Factor Graphs Jeongmin Lee Sunkyung Park Minji Lee Dongjun Lee 125 0 0 08 Mar 2025
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo Hyunsu Kim G. Nam Chulhee Yun Hongseok Yang Juho Lee BDL UQCV 145 0 0 02 Mar 2025
Advancing calibration for stochastic agent-based models in epidemiology with Stein variational inference and Gaussian process surrogates Connor Robertson Cosmin Safta Nicholson T. Collier J. Ozik Jaideep Ray 129 0 0 26 Feb 2025
Stein Discrepancy for Unsupervised Domain Adaptation Anneke von Seeger Dongmian Zou Gilad Lerman 254 0 0 24 Feb 2025
Empirical Bayes Estimation with Side Information: A Nonparametric Integrative Tweedie Approach Jiajun Luo Trambak Banerjee Gourab Mukherjee Wenguang Sun 173 0 0 17 Feb 2025