MULTIPLE INSTANCE LEARNING FRAMEWORK CAN FACILITATE EXPLAINABILITY IN MURMUR DETECTION.



Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience

Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the Toys experiments based on simulations.However, since it is technically demanding to model all components of an experiment, traditional approaches to modeling reduce the experimental se

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Using pupae as appetitive reinforcement to study visual and tactile associative learning in the Ponerine ant Diacamma indicum

Abstract Associative learning is of great importance to animals, as it enhances their ability to navigate, forage, evade predation and improve fitness.Even though associative learning abilities of Hymenopterans have been explored, many of these studies offered food as appetitive reinforcement.In the current study, we focus on tactile and visual cue

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