Scalable Variational Gaussian Process Classification

7 November 2014

Papers citing "Scalable Variational Gaussian Process Classification"

50 / 337 papers shown

Title
Learning Multiscale Non-stationary Causal Structures Gabriele DÁcunto G. D. F. Morales P. Bajardi Francesco Bonchi CML AI4TS 56 4 0 31 Aug 2022
Fast emulation of density functional theory simulations using approximate Gaussian processes S. Stetzler M. Grosskopf E. Lawrence 31 0 0 24 Aug 2022
Virgo: Scalable Unsupervised Classification of Cosmological Shock Waves Max Lamparth Ludwig M. Böss U. Steinwandel K. Dolag 15 0 0 14 Aug 2022
Learning inducing points and uncertainty on molecular data by scalable variational Gaussian processes Mikhail Tsitsvero Mingoo Jin Andrey Lyalin 25 0 0 16 Jul 2022
Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes Gregory W. Benton Wesley J. Maddox A. Wilson AI4TS 38 3 0 13 Jul 2022
Markovian Gaussian Process Variational Autoencoders Harrison Zhu Carles Balsells Rodas Yingzhen Li BDL AI4TS 108 17 0 12 Jul 2022
Parametric and Multivariate Uncertainty Calibration for Regression and Object Detection Fabian Küppers Jonas Schneider Anselm Haselhoff UQCV 83 8 0 04 Jul 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
Additive Gaussian Processes Revisited Xiaoyu Lu A. Boukouvalas J. Hensman 46 23 0 20 Jun 2022
Scalable Deep Gaussian Markov Random Fields for General Graphs Joel Oskarsson Per Sidén Fredrik Lindsten BDL 34 4 0 10 Jun 2022
Cooperative Multi-Agent Trajectory Generation with Modular Bayesian Optimization Gilhyun Ryou E. Tal S. Karaman 59 4 0 01 Jun 2022
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification Juan Maroñas Daniel Hernández-Lobato 71 6 0 30 May 2022
Fast Gaussian Process Posterior Mean Prediction via Local Cross Validation and Precomputation Alec M. Dunton Benjamin W. Priest Amanda Muyskens GP 55 3 0 22 May 2022
Bayesian Active Learning with Fully Bayesian Gaussian Processes Christoffer Riis Francisco Antunes F. B. Hüttel C. L. Azevedo Francisco Câmara Pereira GP 91 24 0 20 May 2022
Scalable Stochastic Parametric Verification with Stochastic Variational Smoothed Model Checking Luca Bortolussi Francesca Cairoli Ginevra Carbone Paolo Pulcini 89 1 0 11 May 2022
Efficient Learning of Inverse Dynamics Models for Adaptive Computed Torque Control David Jorge Gabriella Pizzuto M. Mistry 41 3 0 10 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 228 51 0 01 May 2022
A Gaussian Process Model for Opponent Prediction in Autonomous Racing Edward L. Zhu F. L. Busch Jake Johnson Francesco Borrelli 59 18 0 26 Apr 2022
A piece-wise constant approximation for non-conjugate Gaussian Process models Sarem Seitz 19 0 0 22 Apr 2022
Gaussian Processes for Missing Value Imputation B. Jafrasteh Daniel Hernández-Lobato Simón Pedro Lubián López Isabel Benavente-Fernández GP 64 16 0 10 Apr 2022
Hybrid Transfer in Deep Reinforcement Learning for Ads Allocation Zehua Wang Guogang Liao Xiaowen Shi Xiaoxu Wu Wei Shen Bingqin Zhu Yongkang Wang Xingxing Wang Dong Wang 36 5 0 02 Apr 2022
Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation Benjamin Letham Phillip Guan Chase Tymms E. Bakshy Michael Shvartsman 63 11 0 18 Mar 2022
Web Mining to Inform Locations of Charging Stations for Electric Vehicles Philipp Hummler Christof Naumzik Stefan Feuerriegel 19 5 0 10 Mar 2022
Data-efficient learning of object-centric grasp preferences Yoann Fleytoux Anji Ma S. Ivaldi Jean-Baptiste Mouret 85 5 0 01 Mar 2022
Adaptive Cholesky Gaussian Processes Simon Bartels Kristoffer Stensbo-Smidt Pablo Moreno-Muñoz Wouter Boomsma J. Frellsen Søren Hauberg 78 3 0 22 Feb 2022
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression Giacomo Meanti Luigi Carratino Ernesto De Vito Lorenzo Rosasco 61 13 0 17 Jan 2022
Dual Parameterization of Sparse Variational Gaussian Processes Vincent Adam Paul E. Chang Mohammad Emtiyaz Khan Arno Solin 89 23 0 05 Nov 2021
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data Andrew Jesson P. Tigas Joost R. van Amersfoort Andreas Kirsch Uri Shalit Y. Gal CML 109 32 0 03 Nov 2021
Spatio-Temporal Variational Gaussian Processes Oliver Hamelijnck William J. Wilkinson Niki A. Loppi Arno Solin Theodoros Damoulas AI4TS 72 35 0 02 Nov 2021
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees William J. Wilkinson Simo Särkkä Arno Solin BDL 83 16 0 02 Nov 2021
Scalable Inference in SDEs by Direct Matching of the Fokker-Planck-Kolmogorov Equation Arno Solin Ella Tamir Prakhar Verma 57 19 0 29 Oct 2021
Conditioning Sparse Variational Gaussian Processes for Online Decision-making Wesley J. Maddox Samuel Stanton A. Wilson 76 31 0 28 Oct 2021
Validating Gaussian Process Models with Simulation-Based Calibration John Mcleod F. Simpson 56 3 0 27 Oct 2021
Modular Gaussian Processes for Transfer Learning P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 34 4 0 26 Oct 2021
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets Felix L. Opolka Yin-Cong Zhi Pietro Lio Xiaowen Dong 46 19 0 25 Oct 2021
Bayesian Meta-Learning Through Variational Gaussian Processes Vivek Myers Nikhil Sardana BDL UQCV 28 4 0 21 Oct 2021
Approximate Latent Force Model Inference Jacob Moss Felix L. Opolka Bianca Dumitrascu Pietro Lio 125 3 0 24 Sep 2021
Self-explaining variational posterior distributions for Gaussian Process models Sarem Seitz BDL 24 0 0 08 Sep 2021
Estimation of Bivariate Structural Causal Models by Variational Gaussian Process Regression Under Likelihoods Parametrised by Normalising Flows Nico Reick Felix Wiewel Alexander Bartler B. Yang CML 22 2 0 06 Sep 2021
Data-Driven Wind Turbine Wake Modeling via Probabilistic Machine Learning Sudharshan Ashwin Renganathan R. Maulik S. Letizia G. Iungo AI4CE 33 19 0 06 Sep 2021
Large-Scale Learning with Fourier Features and Tensor Decompositions Frederiek Wesel Kim Batselier 41 11 0 03 Sep 2021
Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations Vihari Piratla Soumen Chakrabarty Sunita Sarawagi 21 3 0 14 Aug 2021
Input Dependent Sparse Gaussian Processes B. Jafrasteh Carlos Villacampa-Calvo Daniel Hernández-Lobato UQCV 53 5 0 15 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
On the Practicality of Deterministic Epistemic Uncertainty Janis Postels Mattia Segu Tao Sun Luca Sieber Luc Van Gool Feng Yu Federico Tombari UQCV 95 61 0 01 Jul 2021
Valid prediction intervals for regression problems Nicolas Dewolf B. De Baets Willem Waegeman 159 46 0 01 Jul 2021
Personalized Federated Learning with Gaussian Processes Idan Achituve Aviv Shamsian Aviv Navon Gal Chechik Ethan Fetaya FedML 87 103 0 29 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
Amortized Auto-Tuning: Cost-Efficient Bayesian Transfer Optimization for Hyperparameter Recommendation Yuxin Xiao Eric P. Xing Willie Neiswanger 77 5 0 17 Jun 2021
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization Marco Rando Luigi Carratino S. Villa Lorenzo Rosasco 88 6 0 16 Jun 2021