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M. Sc. St-Amand, Jesse

5.523
Section for Computational Sensomotorics
Department of Cognitive Neurology
Hertie Institute for Clinical Brain Research
Centre for Integrative Neuroscience
University Clinic Tübingen
Otfried-Müller-Str. 25
72076 Tübingen, Germany
+4970712989135
jesse.st-amand@uni-tuebingen.de
Jesse St-Amand

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Publications

St-Amand, J. & Giese, M. A. (2023). Variable Selection in GPDMs Using the Information Bottleneck Method. 37th Conference on Neural Information Processing Systems (NeurIPS 2023)..
Variable Selection in GPDMs Using the Information Bottleneck Method
Abstract:

Accurate real-time models of human motion are important for applications in areas such as cognitive science and robotics. Neural networks are often the favored choice, yet their generalization properties are limited, particularly on small data sets. This paper utilizes the Gaussian process dynamical model (GPDM) as an alternative. Despite their successes in various motion tasks, GPDMs face challenges like high computational complexity and the need for many hyperparameters. This work addresses these issues by integrating the information bottleneck (IB) framework with GPDMs. The IB approach aims to optimally balance data fit and generalization through measures of mutual information. Our technique uses IB variable selection as a component of GPLVM back-constraints to reduce parameter count and to select features for latent space optimization, resulting in improved model accuracy.

Type of Publication: Article
Journal: 37th Conference on Neural Information Processing Systems (NeurIPS 2023).
Year: 2023
Full text: PDF Online version
[Bibtex]
St-Amand, J., Taubert, N., Gizzi, L. & Giese, M. A (2022). A Hierarchical Gaussian Process Control Algorithm for Bimanual Coordination with Hand Rehabilitation Devices .
A Hierarchical Gaussian Process Control Algorithm for Bimanual Coordination with Hand Rehabilitation Devices
Authors: St-Amand, Jesse; Taubert, Nick; Gizzi, Leonardo Giese, Martin A.
Type of Publication: In Collection
Organization: IMPRS-IS 2022
Full text: PDF
[Bibtex]
Taubert, N., St-Amand, J., Kumar, P., Gizzi, L. & Giese, M. A. (2020). Reactive Hand Movements from Arm Kinematics and EMG Signals Based on Hierarchical Gaussian Process Dynamical Models. Artificial Neural Networks and Machine Learning – ICANN 2020 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15–18, 2020, Proceedings, Part I. Springer, Berlin(127-140).
Reactive Hand Movements from Arm Kinematics and EMG Signals Based on Hierarchical Gaussian Process Dynamical Models
Type of Publication: Article
Full text: Online version
[Bibtex]
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