Context selectivity with dynamic availability enables lifelong continual learning

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The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

Proteins are foundational biomolecules of life playing a crucial role in a myriad of biological processes. Their function often requires interplay with other biomolecules, including proteins themselves. Protein-protein interactions (PPIs) are essential for ...

Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

Established techniques that enable robots to learn from demonstrations are based on learning a stable dynamical system (DS). To increase the robots' resilience to perturbations during tasks that involve static obstacle avoidance, we propose incorporating b ...

Synaptic plasticity underlies the brain’s ability to learn and adapt. While experiments in brain slices have revealed mechanisms and protocols for the induction of plasticity between pairs of neurons, how these synaptic changes are coordinated in biologica ...

Hyperdimensional (HD) computing is a novel approach to machine learning inspired by neuroscience, which uses vectors in a hyper-dimensional space to represent data and models. This approach has gained significant interest in recent years with applications ...

Humans and animals constantly adapt to their environment over the course of their life. This thesis seeks to integrate various timescales of adaptation, ranging from the adaptation of synaptic connections between spiking neurons (milliseconds), rapid behav ...

Context selectivity with dynamic availability enables lifelong continual learning

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Investigating neural resource allocation in the sensorimotor control of extra limbs

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

Meta-learning to address diverse Earth observation problems across resolutions

Learning Barrier-Certified Polynomial Dynamical Systems for Obstacle Avoidance with Robots

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Hyperdimensional computing for biosignal monitoring: Applications for epilepsy detection

From event-based surprise to lifelong learning. A journey in the timescales of adaptation