Stochastic Variational Inference

29 June 2012

Matt Hoffman

Papers citing "Stochastic Variational Inference"

50 / 1,065 papers shown

Title
Physics-Informed Variational State-Space Gaussian Processes Oliver Hamelijnck Arno Solin Theodoros Damoulas 31 0 0 20 Sep 2024
Amortized Variational Inference for Deep Gaussian Processes Qiuxian Meng Yongyou Zhang 28 0 0 18 Sep 2024
HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models Tingwei Meng Zongren Zou Jérome Darbon George Karniadakis DiffM 43 2 0 15 Sep 2024
Uncertainty Quantification in Seismic Inversion Through Integrated Importance Sampling and Ensemble Methods Luping Qu Mauricio Araya-Polo Laurent Demanet 61 0 0 10 Sep 2024
CRADLE-VAE: Enhancing Single-Cell Gene Perturbation Modeling with Counterfactual Reasoning-based Artifact Disentanglement Seungheun Baek Soyon Park Y. T. Chok Junhyun Lee Jueon Park Mogan Gim Jaewoo Kang CML 43 1 0 09 Sep 2024
Gradient-free variational learning with conditional mixture networks Conor Heins Hao Wu Dimitrije Marković Alexander Tschantz Jeff Beck Christopher L. Buckley BDL 31 2 0 29 Aug 2024
Decentralised Variational Inference Frameworks for Multi-object Tracking on Sensor Network Qing Li Runze Gan S. Godsill 29 0 0 24 Aug 2024
Accelerated Markov Chain Monte Carlo Using Adaptive Weighting Scheme Y Samuel Wang Wenyu Chen Shimin Shan 34 0 0 23 Aug 2024
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology Mario De Florio Zongren Zou Daniele E. Schiavazzi George Karniadakis 31 3 0 13 Aug 2024
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling Jian Xu Shian Du Junmei Yang Qianli Ma Delu Zeng BDL 31 0 0 13 Aug 2024
Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations Jian Xu Zhiqi Lin Min Chen Junmei Yang Delu Zeng John Paisley 32 0 0 12 Aug 2024
A Psychology-based Unified Dynamic Framework for Curriculum Learning Guangyu Meng Qingkai Zeng John P. Lalor Hong-ye Yu 31 0 0 09 Aug 2024
Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling Jian Xu Zhiqi Lin Shigui Li Min Chen Junmei Yang Delu Zeng John Paisley BDL 28 0 0 07 Aug 2024
Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography Vincent C. Scholz Yaohua Zang P. Koutsourelakis 41 3 0 30 Jul 2024
Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes Jingyi Gao Seokhyun Chung FedML 41 0 0 24 Jul 2024
cDP-MIL: Robust Multiple Instance Learning via Cascaded Dirichlet Process Yihang Chen Tsai Hor Chan Guosheng Yin Yuming Jiang Lequan Yu 35 0 0 16 Jul 2024
Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference Xiaoyu Jiang Sokratia Georgaka Magnus Rattray Mauricio A. Alvarez 31 0 0 02 Jul 2024
Electrostatics-based particle sampling and approximate inference Yongchao Huang DiffM 35 2 0 28 Jun 2024
Probabilistic Programming with Programmable Variational Inference McCoy R. Becker Alexander K. Lew Xiaoyan Wang Matin Ghavami Mathieu Huot Martin Rinard Vikash K. Mansinghka 59 3 0 22 Jun 2024
Hierarchical thematic classification of major conference proceedings Arsentii Kuzmin Alexander Aduenko Vadim Strijov 23 0 0 21 Jun 2024
Improving Zero-shot LLM Re-Ranker with Risk Minimization Xiaowei Yuan Zhao Yang Yequan Wang Jun Zhao Kang Liu 33 1 0 19 Jun 2024
Variational Distillation of Diffusion Policies into Mixture of Experts Hongyi Zhou Denis Blessing Ge Li Onur Celik Xiaogang Jia Gerhard Neumann Rudolf Lioutikov DiffM 46 3 0 18 Jun 2024
Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks Tristan Cinquin Robert Bamler UQCV BDL 46 2 0 06 Jun 2024
POAM: Probabilistic Online Attentive Mapping for Efficient Robotic Information Gathering Weizhe (Wesley) Chen Lantao Liu R. Khardon 28 1 0 06 Jun 2024
Understanding Stochastic Natural Gradient Variational Inference Kaiwen Wu Jacob R. Gardner BDL 56 1 0 04 Jun 2024
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos P. Koutsourelakis AI4CE 39 3 0 29 May 2024
Federated Learning for Non-factorizable Models using Deep Generative Prior Approximations Conor Hassan Joshua J Bon Elizaveta Semenova Antonietta Mira Kerrie Mengersen 26 0 0 25 May 2024
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows A. Cabezas Louis Sharrock Christopher Nemeth 34 1 0 23 May 2024
Visual Analysis of Prediction Uncertainty in Neural Networks for Deep Image Synthesis Soumya Dutta Faheem Nizar Ahmad Amaan Ayan Acharya AAML 48 1 0 22 May 2024
Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation Yididiya Y. Nadew Xuhui Fan Christopher J. Quinn 19 2 0 19 May 2024
Scalable Amortized GPLVMs for Single Cell Transcriptomics Data Sarah Zhao Aditya Ravuri V. Lalchand Neil D. Lawrence BDL VLM 23 0 0 06 May 2024
Accelerating Convergence in Bayesian Few-Shot Classification Tianjun Ke Haoqun Cao Feng Zhou 50 0 0 02 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks Yunzhen Feng Tim G. J. Rudner Nikolaos Tsilivis Julia Kempe AAML BDL 43 1 0 27 Apr 2024
Variational Bayesian surrogate modelling with application to robust design optimisation Thomas A. Archbold Ieva Kazlauskaite F. Cirak 25 1 0 23 Apr 2024
Scalable Bayesian Image-on-Scalar Regression for Population-Scale Neuroimaging Data Analysis Yuliang Xu Timothy D. Johnson Thomas E. Nichols Jian Kang 23 0 0 19 Apr 2024
Variational Bayesian Last Layers James Harrison John Willes Jasper Snoek BDL UQCV 63 23 0 17 Apr 2024
Variational Stochastic Gradient Descent for Deep Neural Networks Haotian Chen Anna Kuzina Babak Esmaeili Jakub M. Tomczak 52 0 0 09 Apr 2024
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear Regression Tomoya Wakayama BDL 57 0 0 06 Apr 2024
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation Minglei Yang Pengjun Wang Ming Fan Dan Lu Yanzhao Cao Guannan Zhang AI4CE 27 1 0 31 Mar 2024
Neural Clustering based Visual Representation Learning Guikun Chen Xia Li Yi Yang Wenguan Wang SSL 37 8 0 26 Mar 2024
Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models John Fischer Marko Orescanin Justin Loomis Patrick McClure FedML 51 3 0 22 Mar 2024
Variational Inference of Parameters in Opinion Dynamics Models Jacopo Lenti Fabrizio Silvestri G. D. F. Morales 34 3 0 08 Mar 2024
Scaling up Dynamic Edge Partition Models via Stochastic Gradient MCMC Sikun Yang Heinz Koeppl 26 0 0 29 Feb 2024
Bayesian Differentiable Physics for Cloth Digitalization Deshan Gong Ningtao Mao He Wang AI4CE 32 0 0 27 Feb 2024
Variational Learning is Effective for Large Deep Networks Yuesong Shen Nico Daheim Bai Cong Peter Nickl Gian Maria Marconi ... Rio Yokota Iryna Gurevych Daniel Cremers Mohammad Emtiyaz Khan Thomas Möllenhoff 43 22 0 27 Feb 2024
When in Doubt, Think Slow: Iterative Reasoning with Latent Imagination Martin A Benfeghoul Umais Zahid Qinghai Guo Z. Fountas OffRL LRM 40 2 0 23 Feb 2024
Synthetic location trajectory generation using categorical diffusion models Simon Dirmeier Ye Hong Fernando Pérez-Cruz 21 0 0 19 Feb 2024
Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding Martin Rouault Rémi Bardenet Mylène Maïda 54 0 0 18 Feb 2024
HEAL: Brain-inspired Hyperdimensional Efficient Active Learning Yang Ni Zhuowen Zou Wenjun Huang Hanning Chen William Youngwoo Chung Samuel Cho R. Krishnan Pietro Mercati Mohsen Imani 34 2 0 17 Feb 2024
Variational Entropy Search for Adjusting Expected Improvement Nuojin Cheng Stephen Becker 28 1 0 17 Feb 2024