Convolutional Gaussian Processes

6 September 2017

Papers citing "Convolutional Gaussian Processes"

50 / 56 papers shown

Title
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning Toby Boyne Juan S. Campos Becky D Langdon Jixiang Qing Yilin Xie ... Kim E. Jelfs Sarah Boyall Thomas M. Dixon Linden Schrecker Jose Pablo Folch 12 0 0 09 Jun 2025
Regularized Multi-output Gaussian Convolution Process with Domain Adaptation Wang Xinming Wang Chao Song Xuan Kirby Levi Wu Jianguo 60 7 0 04 Sep 2024
Uncertainty Quantification on Graph Learning: A Survey Chao Chen Chenghua Guo Rui Xu Xiangwen Liao Xi Zhang Sihong Xie Hui Xiong Mohit Bansal AI4CE 86 1 0 23 Apr 2024
Hybrid Modeling Design Patterns Maja Rudolph Stefan Kurz Barbara Rakitsch AI4CE 85 9 0 29 Dec 2023
Gaussian process deconvolution Felipe A. Tobar Arnaud Robert Jorge F. Silva 67 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 89 7 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 60 26 0 11 Nov 2022
Globally Gated Deep Linear Networks Qianyi Li H. Sompolinsky AI4CE 74 11 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 95 0 0 27 Jun 2022
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification Juan Maroñas Daniel Hernández-Lobato 71 6 0 30 May 2022
Learning Interacting Dynamical Systems with Latent Gaussian Process ODEs Çağatay Yıldız M. Kandemir Barbara Rakitsch 127 12 0 24 May 2022
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel Ziyang Jiang Tongshu Zheng Yiling Liu David Carlson 73 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 135 2 0 23 Apr 2022
Geometry-Aware Hierarchical Bayesian Learning on Manifolds Yonghui Fan Yalin Wang 33 2 0 30 Oct 2021
Modular Gaussian Processes for Transfer Learning P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 36 4 0 26 Oct 2021
Pre-trained Gaussian processes for Bayesian optimization Zehao Wang George E. Dahl Kevin Swersky Chansoo Lee Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 151 46 0 16 Sep 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 137 133 0 14 May 2021
Deep Neural Networks as Point Estimates for Deep Gaussian Processes Vincent Dutordoir J. Hensman Mark van der Wilk Carl Henrik Ek Zoubin Ghahramani N. Durrande BDL UQCV 103 31 0 10 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 358 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 86 23 0 12 Apr 2021
The Promises and Pitfalls of Deep Kernel Learning Sebastian W. Ober C. Rasmussen Mark van der Wilk UQCV BDL 82 109 0 24 Feb 2021
Transferring model structure in Bayesian transfer learning for Gaussian process regression Milan Papez A. Quinn 41 12 0 18 Jan 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference Felix Leibfried Vincent Dutordoir S. T. John N. Durrande GP 127 51 0 27 Dec 2020
Guiding Neural Network Initialization via Marginal Likelihood Maximization Anthony S. Tai Chunfeng Huang 22 0 0 17 Dec 2020
Statistical Mechanics of Deep Linear Neural Networks: The Back-Propagating Kernel Renormalization Qianyi Li H. Sompolinsky 174 73 0 07 Dec 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 353 1,939 0 12 Nov 2020
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 102 61 0 08 Nov 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 76 208 0 22 Jun 2020
Deep Latent-Variable Kernel Learning Haitao Liu Yew-Soon Ong Xiaomo Jiang Xiaofang Wang BDL 59 8 0 18 May 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 112 60 0 17 May 2020
Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations Simone Rossi Markus Heinonen Edwin V. Bonilla Zheyan Shen Maurizio Filippone UQCV BDL 42 0 0 06 Mar 2020
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 100 95 0 02 Mar 2020
Graph Convolutional Gaussian Processes For Link Prediction Felix L. Opolka Pietro Lio GNN 81 15 0 11 Feb 2020
Doubly Sparse Variational Gaussian Processes Vincent Adam Stefanos Eleftheriadis N. Durrande A. Artemev J. Hensman 82 26 0 15 Jan 2020
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes Greg Yang 154 202 0 28 Oct 2019
A Fine-Grained Spectral Perspective on Neural Networks Greg Yang Hadi Salman 118 113 0 24 Jul 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 75 77 0 19 Jun 2019
Interpretable deep Gaussian processes with moments Chi-Ken Lu Scott Cheng-Hsin Yang Xiaoran Hao Patrick Shafto 67 19 0 27 May 2019
Graph Convolutional Gaussian Processes Ian Walker Ben Glocker GNN 118 36 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 257 928 0 26 Apr 2019
Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes Xubo Yue Raed Al Kontar 85 17 0 09 Mar 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 161 32 0 15 Feb 2019
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation Greg Yang 185 289 0 13 Feb 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 124 874 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 95 10 0 18 Dec 2018
A Gaussian Process perspective on Convolutional Neural Networks Anastasia Borovykh 81 19 0 25 Oct 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 119 310 0 11 Oct 2018
Deep convolutional Gaussian processes Kenneth Blomqvist Samuel Kaski Markus Heinonen BDL 86 61 0 06 Oct 2018
Bayesian Semi-supervised Learning with Graph Gaussian Processes Yin Cheng Ng Nicolo Colombo Ricardo M. A. Silva BDL 93 90 0 12 Sep 2018
Deep Convolutional Networks as shallow Gaussian Processes Adrià Garriga-Alonso C. Rasmussen Laurence Aitchison BDL UQCV 114 271 0 16 Aug 2018