Scalable Variational Gaussian Process Classification

7 November 2014

Papers citing "Scalable Variational Gaussian Process Classification"

50 / 337 papers shown

Title
From Local Interactions to Global Operators: Scalable Gaussian Process Operator for Physical Systems Sawan Kumar Tapas Tripura R. Nayek S. Chakraborty 7 0 0 18 Jun 2025
Few-Shot Speech Deepfake Detection Adaptation with Gaussian Processes Neta Glazer David Chernin Idan Achituve Sharon Gannot Ethan Fetaya 29 0 0 29 May 2025
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project Pratik Rathore Zachary Frangella Sachin Garg Shaghayegh Fazliani Michał Dereziński Madeleine Udell 55 0 0 19 May 2025
Evaluating Uncertainty in Deep Gaussian Processes Matthijs van der Lende Jeremias Lino Ferrao Niclas Müller-Hof UQCV 70 0 0 24 Apr 2025
Latent Bayesian Optimization via Autoregressive Normalizing Flows Seunghun Lee Jinyoung Park Jaewon Chu Minseo Yoon H. Kim BDL 88 2 0 21 Apr 2025
Surrogate-based optimization of system architectures subject to hidden constraints J. Bussemaker P. Saves N. Bartoli T. Lefebvre Björn Nagel AI4CE 440 2 0 11 Apr 2025
Sparse Gaussian Neural Processes Tommy Rochussen Vincent Fortuin BDL UQCV 189 0 0 02 Apr 2025
Mixed Likelihood Variational Gaussian Processes Kaiwen Wu Craig Sanders Benjamin Letham Phillip Guan 109 0 0 06 Mar 2025
Causal Discovery via Bayesian Optimization Bao Duong Sunil Gupta Thin Nguyen 149 0 0 28 Jan 2025
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies from Simulated Nonparametric Functions Cen-You Li Marc Toussaint Barbara Rakitsch Christoph Zimmer OffRL 444 0 0 26 Jan 2025
Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood Yuta Shikuri GP 101 0 0 23 Dec 2024
Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and Regression Junliang Lyu Yixuan Zhang Xiaoling Lu Feng Zhou FedML 132 1 0 14 Dec 2024
Gearing Gaussian process modeling and sequential design towards stochastic simulators M. Binois A. Fadikar Abby Stevens 147 0 0 10 Dec 2024
Prediction of Acoustic Communication Performance for AUVs using Gaussian Process Classification Yifei Gao Harun Yetkin McMahon James D. Stilwell 46 0 0 12 Nov 2024
Constrained composite Bayesian optimization for rational synthesis of polymeric particles Fanjin Wang Maryam Parhizkar Anthony Harker Mohan Edirisinghe 84 0 0 06 Nov 2024
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference Jonathan Wenger Kaiwen Wu Philipp Hennig Jacob R. Gardner Geoff Pleiss John P. Cunningham 84 7 0 01 Nov 2024
Gaussian Derivative Change-point Detection for Early Warnings of Industrial System Failures Hao Zhao Rong Pan 85 1 0 29 Oct 2024
Deep Q-Exponential Processes Zhi Chang Chukwudi Obite Shuang Zhou Shiwei Lan BDL 60 0 0 29 Oct 2024
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference Paul E. Chang Nasrulloh Loka Daolang Huang Ulpu Remes Samuel Kaski Luigi Acerbi AI4CE 104 8 0 20 Oct 2024
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning Peter Eckmann D. Wu G. Heinzelmann Michael K. Gilson Rose Yu AI4CE 117 0 0 15 Oct 2024
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling Jasmine Bayrooti Carl Henrik Ek Amanda Prorok 186 0 0 07 Oct 2024
Amortized Variational Inference for Deep Gaussian Processes Qiuxian Meng Yongyou Zhang 30 0 0 18 Sep 2024
Towards Gaussian Process for operator learning: an uncertainty aware resolution independent operator learning algorithm for computational mechanics Sawan Kumar R. Nayek Souvik Chakraborty 100 4 0 17 Sep 2024
Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations Jian Xu Zhiqi Lin Min Chen Junmei Yang Delu Zeng John Paisley 55 0 0 12 Aug 2024
Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices Frida Viset Anton Kullberg Frederiek Wesel Arno Solin 104 0 0 05 Aug 2024
Aggregation Models with Optimal Weights for Distributed Gaussian Processes Liam Hebert Sukhdeep S. Sodhi 57 0 0 01 Aug 2024
Gaussian Processes Sampling with Sparse Grids under Additive Schwarz Preconditioner Haoyuan Chen Rui Tuo 62 0 0 01 Aug 2024
Idiographic Personality Gaussian Process for Psychological Assessment Yehu Chen Muchen Xi Jacob Montgomery Joshua Jackson Roman Garnett 21 0 0 06 Jul 2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models Xinxing Shi Thomas Baldwin-McDonald Mauricio A. Álvarez 167 0 0 01 Jul 2024
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features Oliver R. A. Dunbar Nicholas H. Nelsen Maya Mutic 134 7 0 30 Jun 2024
Understanding Stochastic Natural Gradient Variational Inference Kaiwen Wu Jacob R. Gardner BDL 82 2 0 04 Jun 2024
Logistic Variational Bayes Revisited M. Komodromos Marina Evangelou Sarah Filippi BDL 50 0 0 02 Jun 2024
Stein Random Feature Regression Houston Warren Rafael Oliveira Fabio Ramos BDL 92 0 0 01 Jun 2024
SEMF: Supervised Expectation-Maximization Framework for Predicting Intervals Ilia Azizi M. Boldi V. Chavez-Demoulin 133 0 0 28 May 2024
Deep Feature Gaussian Processes for Single-Scene Aerosol Optical Depth Reconstruction Shengjie Liu Lu Zhang 29 2 0 27 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks Yunzhen Feng Tim G. J. Rudner Nikolaos Tsilivis Julia Kempe AAML BDL 106 2 0 27 Apr 2024
Tensor Network-Constrained Kernel Machines as Gaussian Processes Frederiek Wesel Kim Batselier 118 0 0 28 Mar 2024
Multi-Fidelity Reinforcement Learning for Time-Optimal Quadrotor Re-planning Gilhyun Ryou Geoffrey Wang S. Karaman 106 3 0 13 Mar 2024
Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecasting Daniel Iong Matthew McAnear Yuezhou Qu S. Zou Gabor Toth Yang Chen 28 0 0 27 Feb 2024
Re-Envisioning Numerical Information Field Theory (NIFTy.re): A Library for Gaussian Processes and Variational Inference G. Edenhofer Philipp Frank Jakob Roth R. Leike Massin Guerdi L. Scheel-Platz M. Guardiani Vincent Eberle M. Westerkamp T. Ensslin 88 9 0 26 Feb 2024
Global Safe Sequential Learning via Efficient Knowledge Transfer Cen-You Li Olaf Duennbier Marc Toussaint Barbara Rakitsch Christoph Zimmer 108 2 0 22 Feb 2024
Recommendations for Baselines and Benchmarking Approximate Gaussian Processes Sebastian W. Ober A. Artemev Marcel Wagenlander Rudolfs Grobins Mark van der Wilk GP 37 1 0 15 Feb 2024
Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints Yunsheng Tian Ane Zuniga Xinwei Zhang Johannes P. Dürholt Payel Das Jie Chen Wojciech Matusik Mina Konakovic-Lukovic 86 2 0 12 Feb 2024
A Bayesian Gaussian Process-Based Latent Discriminative Generative Decoder (LDGD) Model for High-Dimensional Data Navid Ziaei Behzad Nazari Uri T. Eden A. Widge Ali Yousefi 36 3 0 29 Jan 2024
Efficient Nonparametric Tensor Decomposition for Binary and Count Data Zerui Tao Toshihisa Tanaka Qibin Zhao 69 2 0 15 Jan 2024
Fine-grained Forecasting Models Via Gaussian Process Blurring Effect Sepideh Koohfar Laura Dietz DiffM AI4TS 54 0 0 21 Dec 2023
A Kronecker product accelerated efficient sparse Gaussian Process (E-SGP) for flow emulation Yu Duan M. Eaton Michael Bluck 48 0 0 13 Dec 2023
Sparse Variational Student-t Processes Jian Xu Delu Zeng 118 1 0 09 Dec 2023
Identifiable Feature Learning for Spatial Data with Nonlinear ICA Hermanni Hälvä Jonathan So Richard Turner Aapo Hyvarinen CML 113 3 0 28 Nov 2023
Variational Elliptical Processes Maria B˙ankestad Jens Sjölund Jalil Taghia Thomas B. Schon 66 2 0 21 Nov 2023