Machine Learning

Informed Federated Learning to Train a Robotic Arm Inverse Dynamic Model
Access to real-world robotics data is often constrained by data-sharing restrictions and intellectual-property concerns. This work …
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From data extraction to data-driven dynamic modeling for cobots: A method using multi-objective optimization
This work presents a methodology for creating a dataset to learn the dynamics of a collaborative robot. It fine-tunes …
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A deep learning strategy to identify cell types across species from high-density extracellular recordings.
High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but fail to …
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A generic self-learning emotional framework for machines
A self-learning emotional framework that guides reinforcement-learning agents through an internal representation of recently observed values.
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