Deep Gaussian Processes

2 November 2012

Papers citing "Deep Gaussian Processes"

50 / 189 papers shown

Title
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems Zhidi Lin Ying Li Feng Yin Juan Maroñas Alexandre Thiéry 54 0 0 24 Mar 2025
On the Generalization of Representation Uncertainty in Earth Observation Spyros Kondylatos N. Bountos Dimitrios Michail Xiao Xiang Zhu Gustau Camps-Valls Ioannis Papoutsis 74 1 0 10 Mar 2025
Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective Xueqiong Yuan Jipeng Li E. Kuruoglu UQCV BDL 45 0 0 21 Jan 2025
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 113 0 0 20 Jan 2025
Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data M. Risser M. Noack Hengrui Luo Ronald Pandolfi GP 33 0 0 07 Nov 2024
Residual Deep Gaussian Processes on Manifolds Kacper Wyrwal Andreas Krause Viacheslav Borovitskiy BDL 49 0 0 31 Oct 2024
Federated Neural Nonparametric Point Processes Hui Chen Hengyu Liu Hengyu Liu Xuhui Fan Zhilin Zhao Feng Zhou Christopher J. Quinn Longbing Cao FedML 43 0 0 08 Oct 2024
Deep Kernel Posterior Learning under Infinite Variance Prior Weights Jorge Loría A. Bhadra BDL UQCV 66 0 0 02 Oct 2024
Non-stationary and Sparsely-correlated Multi-output Gaussian Process with Spike-and-Slab Prior Wang Xinming Li Yongxiang Yue Xiaowei Wu Jianguo 26 0 0 05 Sep 2024
Uncertainty-Aware Deep Neural Representations for Visual Analysis of Vector Field Data Atul Kumar S. Garg Soumya Dutta 53 0 0 23 Jul 2024
Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space Tigran Ramazyan M. Hushchyn D. Derkach 34 0 0 16 Jul 2024
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning Arthur Jacot Seok Hoan Choi Yuxiao Wen AI4CE 94 2 0 08 Jul 2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models Xinxing Shi Thomas Baldwin-McDonald Mauricio A. Álvarez 79 0 0 01 Jul 2024
Posterior and variational inference for deep neural networks with heavy-tailed weights Ismael Castillo Paul Egels BDL 60 3 0 05 Jun 2024
Computing conservative probabilities of rare events with surrogates Nicolas Bousquet 27 0 0 26 Mar 2024
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search Yunchuan Zhang Sangwoo Park Osvaldo Simeone 48 5 0 14 Mar 2024
Explainable Learning with Gaussian Processes Kurt Butler Guanchao Feng P. Djuric 39 1 0 11 Mar 2024
Deep Horseshoe Gaussian Processes Ismael Castillo Thibault Randrianarisoa BDL UQCV 44 5 0 04 Mar 2024
Gradient-enhanced deep Gaussian processes for multifidelity modelling Viv Bone Chris van der Heide Kieran Mackle Ingo Jahn P. Dower Chris Manzie 27 1 0 25 Feb 2024
Gaussian process learning of nonlinear dynamics Dongwei Ye Mengwu Guo 20 4 0 19 Dec 2023
Robust and Conjugate Gaussian Process Regression Matias Altamirano F. Briol Jeremias Knoblauch 28 10 0 01 Nov 2023
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks Steven Adriaensen Herilalaina Rakotoarison Samuel G. Müller Frank Hutter BDL 31 19 0 31 Oct 2023
Multi-Response Heteroscedastic Gaussian Process Models and Their Inference Taehee Lee Jun S. Liu 13 1 0 29 Aug 2023
Quantitative CLTs in Deep Neural Networks Stefano Favaro Boris Hanin Domenico Marinucci I. Nourdin G. Peccati BDL 33 12 0 12 Jul 2023
Probabilistic-based Feature Embedding of 4-D Light Fields for Compressive Imaging and Denoising Xianqiang Lyu Junhui Hou 41 3 0 15 Jun 2023
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models Bo-wen Li Alexandar J. Thomson Matthew M. Engelhard David Page David Page BDL AI4CE 24 0 0 27 May 2023
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks Felix Jimenez Matthias Katzfuss BDL UQCV 64 1 0 26 May 2023
Bayes Linear Analysis for Statistical Modelling with Uncertain Inputs Samuel E. Jackson D. Woods 11 0 0 09 May 2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial V. Nemani Luca Biggio Xun Huan Zhen Hu Olga Fink Anh Tran Yan Wang Xiaoge Zhang Chao Hu AI4CE 33 75 0 07 May 2023
Representing Additive Gaussian Processes by Sparse Matrices Lu Zou Haoyuan Chen Liang Ding 28 0 0 29 Apr 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
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes Ba-Hien Tran Babak Shahbaba Stephan Mandt Maurizio Filippone SyDa BDL UQCV 21 5 0 09 Feb 2023
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation Henry B. Moss Sebastian W. Ober Victor Picheny 32 24 0 24 Jan 2023
Multi-view Kernel PCA for Time series Forecasting Arun Pandey Hannes De Meulemeester B. De Moor Johan A. K. Suykens AI4TS 36 5 0 24 Jan 2023
Towards Flexibility and Interpretability of Gaussian Process State-Space Model Zhidi Lin Feng Yin Juan Maroñas 34 7 0 21 Jan 2023
Active Learning of Piecewise Gaussian Process Surrogates Chiwoo Park R. Waelder Bonggwon Kang Benji Maruyama Soondo Hong R. Gramacy GP 27 1 0 20 Jan 2023
Self-Supervised Learning for Data Scarcity in a Fatigue Damage Prognostic Problem A. Akrim C. Gogu R. Vingerhoeds M. Salaün AI4CE 35 23 0 20 Jan 2023
Robust Bayesian Target Value Optimization J. G. Hoffer Sascha Ranftl Bernhard C. Geiger 22 9 0 11 Jan 2023
Learning Continuous Depth Representation via Geometric Spatial Aggregator Xiaohang Wang Xuanhong Chen Bingbing Ni Zhengyan Tong Hang Wang MDE 22 6 0 07 Dec 2022
What's Behind the Mask: Estimating Uncertainty in Image-to-Image Problems Gilad Kutiel Regev Cohen Michael Elad Daniel Freedman UQCV 34 5 0 28 Nov 2022
Multi-fidelity Gaussian Process for Biomanufacturing Process Modeling with Small Data Yuan Sun Winton Nathan-Roberts T. Pham E. Otte U. Aickelin AI4CE 10 4 0 26 Nov 2022
Bayesian Learning for Neural Networks: an algorithmic survey M. Magris Alexandros Iosifidis BDL DRL 35 68 0 21 Nov 2022
Deep Gaussian Processes for Air Quality Inference Aadesh Desai Eshan Gujarathi Saagar Parikh Sachin Yadav Zeel B Patel Nipun Batra 36 2 0 18 Nov 2022
Introduction and Exemplars of Uncertainty Decomposition Shuo Chen UD UQCV PER 30 0 0 17 Nov 2022
Scalable Bayesian Transformed Gaussian Processes Xinran Zhu Leo Huang Cameron Ibrahim E. Lee D. Bindel 27 1 0 20 Oct 2022
Non-Gaussian Process Regression Y. Kindap S. Godsill GP 13 1 0 07 Sep 2022
Bayesian Neural Network Language Modeling for Speech Recognition Boyang Xue Shoukang Hu Junhao Xu Mengzhe Geng Xunying Liu Helen M. Meng UQCV BDL 44 14 0 28 Aug 2022
Interpretable Uncertainty Quantification in AI for HEP Thomas Y. Chen B. Dey A. Ghosh Michael Kagan Brian D. Nord Nesar Ramachandra 33 7 0 05 Aug 2022
Decision SincNet: Neurocognitive models of decision making that predict cognitive processes from neural signals Qi Sun Khuong Vo K. Lui Michael D. Nunez J. Vandekerckhove R. Srinivasan 18 0 0 04 Aug 2022
Infinite-Fidelity Coregionalization for Physical Simulation Shibo Li Zihan Wang Robert M. Kirby Shandian Zhe AI4CE 28 6 0 01 Jul 2022