Papers
1,854 papers found
Maximum likelihood estimation in Gaussian process regression is ill-posed
Toni Karvonen, Chris J. Oates
Multi-view Collaborative Gaussian Process Dynamical Systems
Shiliang Sun, Jingjing Fei, Jing Zhao et al.
Causal Discovery with Unobserved Confounding and Non-Gaussian Data
Y. Samuel Wang, Mathias Drton
Seeded Graph Matching for the Correlated Gaussian Wigner Model via the Projected Power Method
Ernesto Araya, Guillaume Braun, Hemant Tyagi
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
Alexander Terenin, David R. Burt, Artem Artemev et al.
Learning Non-Gaussian Graphical Models via Hessian Scores and Triangular Transport
Ricardo Baptista, Rebecca Morrison, Olivier Zahm et al.
Exploration of the Search Space of Gaussian Graphical Models for Paired Data
Alberto Roverato, Dung Ngoc Nguyen
Bayesian Regression Markets
Thomas Falconer, Jalal Kazempour, Pierre Pinson
Classification of Data Generated by Gaussian Mixture Models Using Deep ReLU Networks
Tian-Yi Zhou, Xiaoming Huo
Pre-trained Gaussian Processes for Bayesian Optimization
Zi Wang, George E. Dahl, Kevin Swersky et al.
Gaussian Mixture Models with Rare Events
Xuetong Li, Jing Zhou, Hansheng Wang
Gaussian Interpolation Flows
Yuan Gao, Jian Huang, and Yuling Jiao
Estimation of Sparse Gaussian Graphical Models with Hidden Clustering Structure
Meixia Lin, Defeng Sun, Kim-Chuan Toh et al.
Hamiltonian Monte Carlo for efficient Gaussian sampling: long and random steps
Simon Apers, Sander Gribling, Dániel Szilágyi
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC
Marko Järvenpää, Jukka Corander
Learning Gaussian DAGs from Network Data
Hangjian Li, Oscar Hernan Madrid Padilla, Qing Zhou
Transfer learning for tensor Gaussian graphical models
Mingyang Ren, Yaoming Zhen, Junhui Wang
Random ReLU Neural Networks as Non-Gaussian Processes
Rahul Parhi, Pakshal Bohra, Ayoub El Biari et al.
Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions
Dapeng Yao, Fangzheng Xie, Yanxun Xu
Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data
Didong Li, Andrew Jones, Sudipto Banerjee et al.
gsplat: An Open-Source Library for Gaussian Splatting
Vickie Ye, Ruilong Li, Justin Kerr et al.
Relaxed Gaussian Process Interpolation: a Goal-Oriented Approach to Bayesian Optimization
Sébastien J. Petit, Julien Bect, Emmanuel Vazquez
Mixtures of Gaussian Process Experts with SMC^2
Teemu Härkönen, Sara Wade, Kody Law et al.
Sketching in High-Dimensional Regression With Big Data Using Gaussian Scale Mixture Priors
Rajarshi Guhaniyogi, Aaron Wolfe Scheffler