2024 "gaussian processes" Papers
12 papers found
Amortized Variational Deep Kernel Learning
Alan Matias, César Lincoln Mattos, Joao Paulo Gomes et al.
ICML 2024poster
A Rate-Distortion View of Uncertainty Quantification
Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen et al.
ICML 2024posterarXiv:2406.10775
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition
Shikai Fang, Qingsong Wen, Yingtao Luo et al.
ICML 2024oralarXiv:2308.14906
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing
Lokesh Nagalapatti, Akshay Iyer, Abir De et al.
AAAI 2024paperarXiv:2401.15447
12
citations
Critical feature learning in deep neural networks
Kirsten Fischer, Javed Lindner, David Dahmen et al.
ICML 2024posterarXiv:2405.10761
Domain Invariant Learning for Gaussian Processes and Bayesian Exploration
Xilong Zhao, Siyuan Bian, Yaoyun Zhang et al.
AAAI 2024paperarXiv:2312.11318
2
citations
Gaussian Processes on Cellular Complexes
Mathieu Alain, So Takao, Brooks Paige et al.
ICML 2024posterarXiv:2311.01198
Gaussian Process Neural Additive Models
Wei Zhang, Brian Barr, John Paisley
AAAI 2024paperarXiv:2402.12518
11
citations
Latent variable model for high-dimensional point process with structured missingness
Maksim Sinelnikov, Manuel Haussmann, Harri Lähdesmäki
ICML 2024posterarXiv:2402.05758
Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning
Vivienne Wang, Tinghuai Wang, wenyan yang et al.
ICML 2024posterarXiv:2406.16707
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
Yingyi Chen, Qinghua Tao, Francesco Tonin et al.
ICML 2024posterarXiv:2402.01476
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato
ICML 2024posterarXiv:2302.12565