Convolutional Gaussian Processes

6 September 2017

Papers citing "Convolutional Gaussian Processes"

39 / 39 papers shown

Title
Regularized Multi-output Gaussian Convolution Process with Domain Adaptation Wang Xinming Wang Chao Song Xuan Kirby Levi Wu Jianguo 21 7 0 04 Sep 2024
Hybrid Modeling Design Patterns Maja Rudolph Stefan Kurz Barbara Rakitsch AI4CE 38 8 0 29 Dec 2023
Gaussian process deconvolution Felipe A. Tobar Arnaud Robert Jorge F. Silva 33 5 0 08 May 2023
Actually Sparse Variational Gaussian Processes Harry Jake Cunningham Daniel Augusto R. M. A. de Souza So Takao Mark van der Wilk M. Deisenroth 32 5 0 11 Apr 2023
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization Jose Pablo Folch Robert M. Lee B. Shafei David Walz Calvin Tsay Mark van der Wilk Ruth Misener 36 23 0 11 Nov 2022
Globally Gated Deep Linear Networks Qianyi Li H. Sompolinsky AI4CE 27 10 0 31 Oct 2022
Distributional Gaussian Processes Layers for Out-of-Distribution Detection S. Popescu D. Sharp James H. Cole Konstantinos Kamnitsas Ben Glocker OOD 29 0 0 27 Jun 2022
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification Juan Maroñas Daniel Hernández-Lobato 22 6 0 30 May 2022
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel Ziyang Jiang Tongshu Zheng Yiling Liu David Carlson 32 4 0 15 May 2022
Unsupervised Restoration of Weather-affected Images using Deep Gaussian Process-based CycleGAN R. Yasarla Vishwanath A. Sindagi Vishal M. Patel 40 2 0 23 Apr 2022
Geometry-Aware Hierarchical Bayesian Learning on Manifolds Yonghui Fan Yalin Wang 18 2 0 30 Oct 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 35 124 0 14 May 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure Samuel Kim Peter Y. Lu Charlotte Loh Jamie Smith Jasper Snoek M. Soljavcić BDL AI4CE 148 17 0 23 Apr 2021
GPflux: A Library for Deep Gaussian Processes Vincent Dutordoir Hugh Salimbeni Eric Hambro John Mcleod Felix Leibfried A. Artemev Mark van der Wilk J. Hensman M. Deisenroth S. T. John GP 35 23 0 12 Apr 2021
The Promises and Pitfalls of Deep Kernel Learning Sebastian W. Ober C. Rasmussen Mark van der Wilk UQCV BDL 21 107 0 24 Feb 2021
Transferring model structure in Bayesian transfer learning for Gaussian process regression Milan Papez A. Quinn 24 11 0 18 Jan 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference Felix Leibfried Vincent Dutordoir S. T. John N. Durrande GP 42 49 0 27 Dec 2020
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 18 58 0 08 Nov 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 37 199 0 22 Jun 2020
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks Sujay Thakur Cooper Lorsung Yaniv Yacoby Finale Doshi-Velez Weiwei Pan BDL UQCV 33 4 0 21 Jun 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 26 60 0 17 May 2020
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 42 94 0 02 Mar 2020
Graph Convolutional Gaussian Processes For Link Prediction Felix L. Opolka Pietro Lio GNN 27 15 0 11 Feb 2020
Doubly Sparse Variational Gaussian Processes Vincent Adam Stefanos Eleftheriadis N. Durrande A. Artemev J. Hensman 27 24 0 15 Jan 2020
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO Pablo Morales-Álvarez Pablo Ruiz S. Coughlin Rafael Molina Aggelos K. Katsaggelos 21 14 0 05 Nov 2019
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes Greg Yang 33 193 0 28 Oct 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 38 77 0 19 Jun 2019
Interpretable deep Gaussian processes with moments Chi-Ken Lu Scott Cheng-Hsin Yang Xiaoran Hao Patrick Shafto 26 19 0 27 May 2019
Kernel Mean Matching for Content Addressability of GANs Wittawat Jitkrittum Patsorn Sangkloy Muhammad Waleed Gondal Amit Raj James Hays Bernhard Schölkopf GAN BDL 32 9 0 14 May 2019
Graph Convolutional Gaussian Processes Ian Walker Ben Glocker GNN 22 35 0 14 May 2019
On Exact Computation with an Infinitely Wide Neural Net Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang 53 906 0 26 Apr 2019
Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes Xubo Yue Raed Al Kontar 32 16 0 09 Mar 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 46 854 0 18 Jan 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 20 10 0 18 Dec 2018
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes Roman Novak Lechao Xiao Jaehoon Lee Yasaman Bahri Greg Yang Jiri Hron Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 25 307 0 11 Oct 2018
Learning Invariances using the Marginal Likelihood Mark van der Wilk Matthias Bauer S. T. John J. Hensman 36 83 0 16 Aug 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 24 68 0 06 Jun 2018
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models Jacob R. Kauffmann K. Müller G. Montavon DRL 42 96 0 16 May 2018
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 92 271 0 24 Feb 2014