Gaussian Processes for Big Data

26 September 2013

Papers citing "Gaussian Processes for Big Data"

50 / 604 papers shown

Title
Uncertainty Quantification and Experimental Design for Large-Scale Linear Inverse Problems under Gaussian Process Priors Cédric Travelletti D. Ginsbourger N. Linde 70 4 0 08 Sep 2021
Large-Scale Learning with Fourier Features and Tensor Decompositions Frederiek Wesel Kim Batselier 56 11 0 03 Sep 2021
Optimal Order Simple Regret for Gaussian Process Bandits Sattar Vakili N. Bouziani Sepehr Jalali A. Bernacchia Da-shan Shiu 99 55 0 20 Aug 2021
PI3NN: Out-of-distribution-aware prediction intervals from three neural networks Si-Yuan Liu Pei Zhang Dan Lu Guannan Zhang OODD 65 10 0 05 Aug 2021
Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models Zhiliang Wu Yinchong Yang Peter A. Fasching Volker Tresp BDL 73 10 0 26 Jul 2021
Subset-of-Data Variational Inference for Deep Gaussian-Processes Regression Ayush Jain P. K. Srijith Mohammad Emtiyaz Khan BDL GP 45 0 0 17 Jul 2021
Input Dependent Sparse Gaussian Processes B. Jafrasteh Carlos Villacampa-Calvo Daniel Hernández-Lobato UQCV 53 5 0 15 Jul 2021
The Bayesian Learning Rule Mohammad Emtiyaz Khan Håvard Rue BDL 167 83 0 09 Jul 2021
Scaling Gaussian Processes with Derivative Information Using Variational Inference Misha Padidar Xinran Zhu Leo Huang Jacob R. Gardner D. Bindel BDL 51 18 0 08 Jul 2021
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization Jonathan Wenger Geoff Pleiss Philipp Hennig John P. Cunningham Jacob R. Gardner 122 24 0 01 Jul 2021
Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors Liwei Wang Suraj Yerramilli Akshay Iyer D. Apley Ping Zhu Wei Chen 82 26 0 26 Jun 2021
Deep Gaussian Processes: A Survey Kalvik Jakkala AI4CE GP BDL 78 20 0 21 Jun 2021
Variational multiple shooting for Bayesian ODEs with Gaussian processes Pashupati Hegde Çağatay Yıldız Harri Lähdesmäki Samuel Kaski Markus Heinonen 88 16 0 21 Jun 2021
Combining Pseudo-Point and State Space Approximations for Sum-Separable Gaussian Processes Will Tebbutt Arno Solin Richard Turner 56 8 0 18 Jun 2021
Probabilistic DAG Search Julia Grosse Cheng Zhang Philipp Hennig 48 4 0 16 Jun 2021
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes Sanyam Kapoor Marc Finzi Ke Alexander Wang A. Wilson 74 12 0 12 Jun 2021
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition Shengyang Sun Jiaxin Shi A. Wilson Roger C. Grosse BDL 31 7 0 10 Jun 2021
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data Jens Petersen Gregor Koehler David Zimmerer Hyunjin Park Paul F. Jäger Klaus H. Maier-Hein BDL AI4TS 71 3 0 09 Jun 2021
Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems Haitao Liu Changjun Liu Xiaomo Jiang Xudong Chen Shuhua Yang Xiaofang Wang BDL AI4TS 102 2 0 03 Jun 2021
Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes Veit Wild Motonobu Kanagawa Dino Sejdinovic 81 16 0 02 Jun 2021
Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Network Rui Meng Herbert Lee K. Bouchard 46 2 0 01 Jun 2021
Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning Zhiliang Wu Yinchong Yang Jindong Gu Volker Tresp UQCV MedIm 50 9 0 01 Jun 2021
Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data Shixiang Zhu Alexander W. Bukharin Liyan Xie Khurram Yamin Shihao Yang P. Keskinocak Yao Xie 57 8 0 31 May 2021
Model Selection for Production System via Automated Online Experiments Zhenwen Dai Praveen Chandar G. Fazelnia Ben Carterette M. Lalmas 68 4 0 27 May 2021
Scalable Cross Validation Losses for Gaussian Process Models M. Jankowiak Geoff Pleiss 67 6 0 24 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 139 134 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 106 31 0 10 May 2021
Grey-box models for wave loading prediction D. J. Pitchforth T. Rogers U. T. Tygesen E. Cross 58 33 0 10 May 2021
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation S. Popescu D. Sharp James H. Cole Konstantinos Kamnitsas Ben Glocker 38 5 0 28 Apr 2021
Mixtures of Gaussian Processes for regression under multiple prior distributions Sarem Seitz 15 1 0 19 Apr 2021
Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model Inversion D. Svendsen Pablo Morales-Álvarez A. Ruescas Rafael Molina Gustau Camps-Valls 141 30 0 16 Apr 2021
Sequential Deconfounding for Causal Inference with Unobserved Confounders Tobias Hatt Stefan Feuerriegel CML 97 29 0 16 Apr 2021
Uncertainty-aware Remaining Useful Life predictor Luca Biggio Alexander Wieland M. A. Chao I. Kastanis Olga Fink AI4CE 37 7 0 08 Apr 2021
High-Dimensional Bayesian Optimization with Multi-Task Learning for RocksDB Sami Alabed Eiko Yoneki 65 18 0 30 Mar 2021
Sparse Algorithms for Markovian Gaussian Processes William J. Wilkinson Arno Solin Vincent Adam 62 12 0 19 Mar 2021
Discovery of Physics and Characterization of Microstructure from Data with Bayesian Hidden Physics Models Steven Atkinson Yiming Zhang Liping Wang AI4CE 23 0 0 12 Mar 2021
On MCMC for variationally sparse Gaussian processes: A pseudo-marginal approach Karla Monterrubio-Gómez S. Wade 56 2 0 04 Mar 2021
Kernel Interpolation for Scalable Online Gaussian Processes Samuel Stanton Wesley J. Maddox Ian A. Delbridge A. Wilson GP 65 30 0 02 Mar 2021
Generative Particle Variational Inference via Estimation of Functional Gradients Neale Ratzlaff Qinxun Bai Fuxin Li Wenyuan Xu BDL DRL 123 0 0 01 Mar 2021
Hierarchical Inducing Point Gaussian Process for Inter-domain Observations Luhuan Wu Andrew C. Miller Lauren Anderson Geoff Pleiss David M. Blei John P. Cunningham 73 9 0 28 Feb 2021
Highly Efficient Representation and Active Learning Framework and Its Application to Imbalanced Medical Image Classification Heng Hao H. Moon Sima Didari J. Woo P. Bangert AI4TS 35 0 0 25 Feb 2021
Healing Products of Gaussian Processes Samuel N. Cohen R. Mbuvha T. Marwala M. Deisenroth GP 47 0 0 14 Feb 2021
Bias-Free Scalable Gaussian Processes via Randomized Truncations Andres Potapczynski Luhuan Wu D. Biderman Geoff Pleiss John P. Cunningham 84 20 0 12 Feb 2021
Structure-preserving Gaussian Process Dynamics K. Ensinger Friedrich Solowjow Sebastian Ziesche Michael Tiemann Sebastian Trimpe 73 9 0 02 Feb 2021
Gaussian Experts Selection using Graphical Models Hamed Jalali Martin Pawelczyk Gjerji Kasneci 68 3 0 02 Feb 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference Felix Leibfried Vincent Dutordoir S. T. John N. Durrande GP 164 52 0 27 Dec 2020
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior Anh Tong Toan M. Tran Hung Bui Jaesik Choi 58 3 0 21 Dec 2020
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? Antoine Grosnit Alexander I. Cowen-Rivers Rasul Tutunov Ryan-Rhys Griffiths Jun Wang Haitham Bou-Ammar 105 14 0 15 Dec 2020
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes A. Benavoli Dario Azzimonti Dario Piga 67 15 0 12 Dec 2020
Bayesian Graph Neural Networks for Molecular Property Prediction George Lamb Brooks Paige 75 12 0 25 Nov 2020