Safe Active Learning and Probabilistic Design of Experiment for Autonomous Hydraulic Excavators

M Dio, O Demir, A Trachte… - 2023 IEEE/RSJ …, 2023 - ieeexplore.ieee.org
Recently, data-driven and hybrid control of hydraulic cylinders for excavator assistance
functions have been in the focus of many research papers. To ensure an accurate behavior …

GP-PCS: One-Shot Feature-Preserving Point Cloud Simplification with Gaussian Processes on Riemannian Manifolds

S Pathak, T Baldwin-McDonald, S Sels… - … Conference on Pattern …, 2025 - Springer
The processing, storage and transmission of large-scale point clouds is an ongoing
challenge in the computer vision community which hinders progress in the application of 3D …

[PDF][PDF] One-shot Feature-Preserving Point Cloud Simplification with Gaussian Processes on Riemannian Manifolds.

S Pathak, TM McDonald, R Penne - CoRR, 2023 - tomcdonald.github.io
The processing, storage and transmission of large-scale point clouds is an ongoing
challenge in the computer vision community which hinders progress in the application of 3D …

Efficient Recomputation of Marginal Likelihood upon Adding Training Data in Gaussian Processes and Simulator Fusion

Y Ohtsubo, H Ohashi - openreview.net
To reduce generalization loss in line with the bias-variance trade-off, machine learning
engineers should construct models based on their knowledge of the modeling target and, as …

Fast Computation of Gaussian Processes Augmented by Synthetic Simulator Data

Y Ohtsubo, H Ohashi - openreview.net
When the amount of training data is limited, augmenting it with generated data from a
simulator can be a beneficial approach to improving prediction accuracy. However, there are …

Machine Unlearning and hyperparameters optimization in Gaussian Process regression

M Manthe - 2021 - diva-portal.org
The establishment of the General Data Protection Regulation (GDPR) in Europe in 2018,
including the" Right to be Forgotten" poses important questions about the necessity of …