4 citations · 8 across the 6 of their papers we have counts for
3 papers · 1 filter
Thin and Deep Gaussian Processes
Daniel Augusto de Souza, Alexander Nikitin, ST John +6
Gaussian processes (GPs) can provide a principled approach to uncertainty quantification with easy-to-interpret kernel hyperparameters, such as the lengthscale, which controls the…
ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Mustafa Hajij, Helen Jenne +53
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competi…
TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
Alexander Nikitin, Letizia Iannucci, Samuel Kaski
Temporally indexed data are essential in a wide range of fields and of interest to machine learning researchers. Time series data, however, are often scarce or highly sensitive, wh…