Student-t Processes as Alternatives to Gaussian Processes

18 February 2014

Papers citing "Student-t Processes as Alternatives to Gaussian Processes"

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Title
From Target Tracking to Targeting Track -- Part III: Stochastic Process Modeling and Online Learning Tiancheng Li Jingyuan Wang Guchong Li Dengwei Gao 55 2 0 03 Mar 2025
Student-t processes as infinite-width limits of posterior Bayesian neural networks Francesco Caporali Stefano Favaro Dario Trevisan BDL 230 0 0 06 Feb 2025
Robust Gaussian Processes via Relevance Pursuit Sebastian Ament Elizabeth Santorella David Eriksson Ben Letham Maximilian Balandat E. Bakshy GP 41 0 0 08 Jan 2025
Gearing Gaussian process modeling and sequential design towards stochastic simulators M. Binois A. Fadikar Abby Stevens 82 0 0 10 Dec 2024
Information Geometry and Beta Link for Optimizing Sparse Variational Student-t Processes Jian Xu Delu Zeng John Paisley 19 0 0 13 Aug 2024
A Learning-Based Model Predictive Contouring Control for Vehicle Evasive Manoeuvres A. Bertipaglia Mohsen Alirezaei R. Happee Barys Shyrokau 20 0 0 08 Aug 2024
Computationally efficient multi-level Gaussian process regression for functional data observed under completely or partially regular sampling designs Adam Gorm Hoffmann C. T. Ekstrøm Andreas Kryger Jensen 15 0 0 19 Jun 2024
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties V. ArunKumarA. A. Shilton Sunil R. Gupta Santu Rana S. Greenhill Svetha Venkatesh 13 4 0 27 Feb 2024
Logistic-beta processes for dependent random probabilities with beta marginals Changwoo J. Lee Alessandro Zito Huiyan Sang David B. Dunson 11 0 0 10 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 47 27 0 01 Feb 2024
Beyond Regrets: Geometric Metrics for Bayesian Optimization Jungtaek Kim 29 0 0 03 Jan 2024
Robust Estimation of Causal Heteroscedastic Noise Models Quang-Duy Tran Bao Duong Phuoc Nguyen Thin Nguyen 19 1 0 15 Dec 2023
Sparse Variational Student-t Processes Jian Xu Delu Zeng 28 1 0 09 Dec 2023
Identifiable Feature Learning for Spatial Data with Nonlinear ICA Hermanni Hälvä Jonathan So Richard Turner Aapo Hyvarinen CML 42 2 0 28 Nov 2023
Variational Elliptical Processes Maria B˙ankestad Jens Sjölund Jalil Taghia Thomas B. Schon 30 2 0 21 Nov 2023
Online Student- $t$ Processes with an Overall-local Scale Structure for Modelling Non-stationary Data Taole Sha Michael Minyi Zhang 16 0 0 01 Nov 2023
Local Kernel Renormalization as a mechanism for feature learning in overparametrized Convolutional Neural Networks R. Aiudi R. Pacelli A. Vezzani R. Burioni P. Rotondo MLT 21 15 0 21 Jul 2023
PFNs4BO: In-Context Learning for Bayesian Optimization Samuel G. Müller Matthias Feurer Noah Hollmann Frank Hutter 30 34 0 27 May 2023
Deep Stochastic Processes via Functional Markov Transition Operators Jin Xu Emilien Dupont Kaspar Martens Tom Rainforth Yee Whye Teh 38 4 0 24 May 2023
Bayesian inference with finitely wide neural networks Chi-Ken Lu BDL 37 0 0 06 Mar 2023
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks Jiayu Yao Yaniv Yacoby Beau Coker Weiwei Pan Finale Doshi-Velez 24 1 0 16 Nov 2022
MARS: Meta-Learning as Score Matching in the Function Space Krunoslav Lehman Pavasovic Jonas Rothfuss Andreas Krause BDL 37 4 0 24 Oct 2022
Bayesian Learning via Q-Exponential Process Shuyi Li Michael O'Connor Shiwei Lan 30 2 0 14 Oct 2022
Non-Gaussian Process Regression Y. Kindap S. Godsill GP 13 1 0 07 Sep 2022
Scale invariant process regression: Towards Bayesian ML with minimal assumptions Matthias Wieler 13 0 0 22 Aug 2022
A Two-Stage Bayesian Optimisation for Automatic Tuning of an Unscented Kalman Filter for Vehicle Sideslip Angle Estimation A. Bertipaglia Barys Shyrokau Mohsen Alirezaei Department of Mechanical Engineering 45 14 0 30 Jun 2022
Spatial meshing for general Bayesian multivariate models M. Peruzzi David B. Dunson 90 6 0 25 Jan 2022
Non-smooth Bayesian Optimization in Tuning Problems Hengrui Luo J. Demmel Younghyun Cho Xin Li Yang Liu 25 13 0 15 Sep 2021
Scale Mixtures of Neural Network Gaussian Processes Hyungi Lee Eunggu Yun Hongseok Yang Juho Lee UQCV BDL 13 7 0 03 Jul 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
One-parameter family of acquisition functions for efficient global optimization T. Kanazawa 35 2 0 26 Apr 2021
Partially Observed Exchangeable Modeling Yang Li Junier B. Oliva 20 5 0 11 Feb 2021
Explaining Inference Queries with Bayesian Optimization Brandon Lockhart Jinglin Peng Weiyuan Wu Jiannan Wang Eugene Wu 21 7 0 10 Feb 2021
Deep kernel processes Laurence Aitchison Adam X. Yang Sebastian W. Ober BDL 24 41 0 04 Oct 2020
t-Soft Update of Target Network for Deep Reinforcement Learning Taisuke Kobayashi Wendyam Eric Lionel Ilboudo 87 50 0 25 Aug 2020
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure S. Iwazaki Yu Inatsu Ichiro Takeuchi TPM 29 11 0 22 Jun 2020
Energy-Based Processes for Exchangeable Data Mengjiao Yang Bo Dai H. Dai Dale Schuurmans 22 12 0 17 Mar 2020
The Elliptical Processes: a Family of Fat-tailed Stochastic Processes Maria Bånkestad Jens Sjölund Jalil Taghia Thomas B. Schon 23 1 0 13 Mar 2020
Conditional Deep Gaussian Processes: multi-fidelity kernel learning Chi-Ken Lu Patrick Shafto 19 5 0 07 Feb 2020
Transport Gaussian Processes for Regression Gonzalo Rios GP 21 6 0 30 Jan 2020
TPLVM: Portfolio Construction by Student's $t$ -process Latent Variable Model Y. Uchiyama Kei Nakagawa 19 9 0 29 Jan 2020
Robust Gaussian Process Regression with a Bias Model Chiwoo Park David J. Borth Nicholas S. Wilson Chad N. Hunter F. Friedersdorf 25 27 0 14 Jan 2020
Heteroscedastic Gaussian Process Regression on the Alkenone over Sea Surface Temperatures Etienne Brangbour Marco Chini 11 8 0 18 Dec 2019
Kalman Filter Tuning with Bayesian Optimization Zhaozhong Chen Nisar R. Ahmed S. Julier Christoffer Heckman 11 13 0 17 Dec 2019
Set Flow: A Permutation Invariant Normalizing Flow Kashif Rasul Ingmar Schuster Roland Vollgraf Urs M. Bergmann BDL 3DPC DRL 17 5 0 06 Sep 2019
A review of Approximate Bayesian Computation methods via density estimation: inference for simulator-models C. Grazian Yanan Fan TPM 24 22 0 06 Sep 2019
Stochastic quasi-Newton with line-search regularization A. Wills Thomas B. Schon ODL 19 21 0 03 Sep 2019
Interpretable deep Gaussian processes with moments Chi-Ken Lu Scott Cheng-Hsin Yang Xiaoran Hao Patrick Shafto 18 19 0 27 May 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 22 235 0 14 Mar 2019
Financial Applications of Gaussian Processes and Bayesian Optimization Joan Gonzalvez Edmond Lezmi T. Roncalli Jiali Xu 20 54 0 12 Mar 2019