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Bayesian Manifold Regression

3 May 2013

Papers citing "Bayesian Manifold Regression"

25 / 25 papers shown

Title
Deep Horseshoe Gaussian Processes Ismael Castillo Thibault Randrianarisoa BDL UQCV 108 5 0 04 Mar 2024
Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds Paul Rosa Viacheslav Borovitskiy Alexander Terenin Judith Rousseau 96 8 0 19 Sep 2023
Random Smoothing Regularization in Kernel Gradient Descent Learning Liang Ding Tianyang Hu Jiahan Jiang Donghao Li Wei Cao Yuan Yao 64 6 0 05 May 2023
Pairwise Ranking with Gaussian Kernels Guanhang Lei Lei Shi 89 2 0 06 Apr 2023
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics Mu Niu Zhenwen Dai P. Cheung Yizhu Wang 65 5 0 16 Jan 2023
Generalized Fiducial Inference on Differentiable Manifolds Alexander C. Murph Jan Hannig Jonathan P. Williams 59 3 0 30 Sep 2022
Optimal recovery and uncertainty quantification for distributed Gaussian process regression Amine Hadji Tammo Hesselink Botond Szabó 72 3 0 06 May 2022
Estimation of a regression function on a manifold by fully connected deep neural networks Michael Kohler S. Langer U. Reif 68 5 0 20 Jul 2021
Intrinsic Dimension Adaptive Partitioning for Kernel Methods Thomas Hamm Ingo Steinwart 28 3 0 16 Jul 2021
Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition Guohao Shen Yuling Jiao Yuanyuan Lin J. Horowitz Jian Huang 260 23 0 10 Jul 2021
Gaussian Process Subspace Regression for Model Reduction Ruda Zhang Simon Mak David B. Dunson GP 40 5 0 09 Jul 2021
Deep Nonparametric Regression on Approximate Manifolds: Non-Asymptotic Error Bounds with Polynomial Prefactors Yuling Jiao Guohao Shen Yuanyuan Lin Jian Huang 121 52 0 14 Apr 2021
Airflow recovery from thoracic and abdominal movements using Synchrosqueezing Transform and Locally Stationary Gaussian Process Regression Whitney K. Huang Yu-Min Chung Yu-Bo Wang J. Mandel Hau‐Tieng Wu 60 5 0 11 Aug 2020
Statistical Inference in Mean-Field Variational Bayes Wei Han Yun Yang 48 18 0 04 Nov 2019
Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space Taiji Suzuki Atsushi Nitanda 93 63 0 28 Oct 2019
Gaussian Processes with Errors in Variables: Theory and Computation Shuang Zhou D. Pati Tianying Wang Yun Yang R. Carroll 71 4 0 14 Oct 2019
Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality Ryumei Nakada Masaaki Imaizumi AI4CE 73 38 0 04 Jul 2019
Diffusion $K$ -means clustering on manifolds: provable exact recovery via semidefinite relaxations Xiaohui Chen Yun Yang 71 16 0 11 Mar 2019
When Locally Linear Embedding Hits Boundary Hau‐Tieng Wu Nan Wu 68 11 0 11 Nov 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 144 697 0 03 Jul 2018
Gaussian Process Landmarking on Manifolds Tingran Gao S. Kovalsky Ingrid Daubechies 127 39 0 09 Feb 2018
Frequentist coverage and sup-norm convergence rate in Gaussian process regression Yun Yang A. Bhattacharya D. Pati 78 54 0 16 Aug 2017
Probabilistic Integration: A Role in Statistical Computation? François‐Xavier Briol Chris J. Oates Mark Girolami Michael A. Osborne Dino Sejdinovic 161 53 0 03 Dec 2015
Fast Gaussian Process Regression for Big Data Sourish Das Sasanka Roy R. Sambasivan GP 95 48 0 17 Sep 2015
Minimax-optimal nonparametric regression in high dimensions Yun Yang S. Tokdar 111 93 0 28 Jan 2014