Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences

6 July 2018

Motonobu Kanagawa

Philipp Hennig

Dino Sejdinovic

Bharath K. Sriperumbudur

BDL

ArXiv PDF HTML

Papers citing "Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences"

25 / 75 papers shown

Title
Optimal Order Simple Regret for Gaussian Process Bandits Sattar Vakili N. Bouziani Sepehr Jalali A. Bernacchia Da-shan Shiu 39 51 0 20 Aug 2021
Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo Ziang Niu J. Meier F. Briol 42 12 0 22 Jun 2021
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios Alessandro Favero Francesco Cagnetta Matthieu Wyart 35 31 0 16 Jun 2021
Bayesian Optimistic Optimisation with Exponentially Decaying Regret Hung The Tran Sunil R. Gupta Santu Rana Svetha Venkatesh 24 3 0 10 May 2021
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression Christian Fiedler C. Scherer Sebastian Trimpe GP 31 65 0 06 May 2021
Bayesian Numerical Methods for Nonlinear Partial Differential Equations Junyang Wang Jon Cockayne O. Chkrebtii T. Sullivan Chris J. Oates 63 19 0 22 Apr 2021
Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks Thanh Nguyen-Tang Sunil R. Gupta Hung The Tran Svetha Venkatesh OffRL 70 7 0 11 Mar 2021
Small Sample Spaces for Gaussian Processes Toni Karvonen 24 13 0 04 Mar 2021
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 18 58 0 08 Nov 2020
Stable ResNet Soufiane Hayou Eugenio Clerico Bo He George Deligiannidis Arnaud Doucet Judith Rousseau ODL SSeg 46 51 0 24 Oct 2020
On Information Gain and Regret Bounds in Gaussian Process Bandits Sattar Vakili Kia Khezeli Victor Picheny GP 29 128 0 15 Sep 2020
A Kernel Two-Sample Test for Functional Data George Wynne Andrew B. Duncan 25 42 0 25 Aug 2020
Deterministic error bounds for kernel-based learning techniques under bounded noise E. Maddalena Paul Scharnhorst Colin N. Jones 33 45 0 10 Aug 2020
On the Similarity between the Laplace and Neural Tangent Kernels Amnon Geifman A. Yadav Yoni Kasten Meirav Galun David Jacobs Ronen Basri 25 89 0 03 Jul 2020
Sparse Gaussian Processes with Spherical Harmonic Features Vincent Dutordoir N. Durrande J. Hensman 27 54 0 30 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 38 82 0 15 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 13 34 0 09 Jun 2020
Universal Robust Regression via Maximum Mean Discrepancy Pierre Alquier Mathieu Gerber 45 15 0 01 Jun 2020
Bayesian ODE Solvers: The Maximum A Posteriori Estimate Filip Tronarp Simo Sarkka Philipp Hennig 45 42 0 01 Apr 2020
Information Directed Sampling for Linear Partial Monitoring Johannes Kirschner Tor Lattimore Andreas Krause 24 46 0 25 Feb 2020
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions Toni Karvonen George Wynne Filip Tronarp Chris J. Oates Simo Särkkä 42 39 0 29 Jan 2020
On the optimality of kernels for high-dimensional clustering L. C. Vankadara D. Ghoshdastidar 39 11 0 01 Dec 2019
Uncertainty Estimates for Ordinal Embeddings Michael Lohaus Philipp Hennig U. V. Luxburg 39 6 0 27 Jun 2019
Spatial Analysis Made Easy with Linear Regression and Kernels Philip Milton E. Giorgi Samir Bhatt 27 18 0 22 Feb 2019
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann Arthur Gretton BDL 112 325 0 09 Feb 2016