In learning-to-learn the goal is to infer a learning algorithm that works well on a class of tasks sampled from an unknown meta distribution. In cont…
With strongly bound and stable excitons at room temperature, single-layer, two-dimensional organic-inorganic hybrid perovskites are viable semiconduc…
We present a new method to relocalize the 6DOF pose of an event camera solely based on the event stream. Our method first creates the event image fro…
Human beings can make use of various reactive strategies, e.g. foot location adjustment and upper-body inclination, to keep balance while walking und…
Articulated objects like doors, drawers, valves, and tools are pervasive in our everyday unstructured dynamic environments. Articulation models descr…
The dynamics of a quasi two-dimensional isotropic droplet in a cholesteric liquid crystal medium under symmetric shear flow is studied by lattice Bol…
Owing to both electronic and dielectric confinement effects, two-dimensional organic-inorganic hybrid perovskites sustain strongly bound excitons at …
We explore the electronic structure, orbital character and topological aspect of a monolayer MoS$_2$ nanoribbon using tight-binding (TB) and low-ener…
Somatosensory inputs can be grossly divided into tactile (or cutaneous) and proprioceptive -- the former conveying information about skin stimulation…
We consider object recognition in the context of lifelong learning, where a robotic agent learns to discriminate between a growing number of object c…
Despite surveillance systems are becoming increasingly ubiquitous in our living environment, automated surveillance, currently based on video sensory…
We propose and study a novel stochastic inertial primal-dual approach to solve composite optimization problems. These latter problems arise naturally…
In many applications of finance, biology and sociology, complex systems involve entities interacting with each other. These processes have the peculi…
We present a novel algorithm to estimate the barycenter of arbitrary probability distributions with respect to the Sinkhorn divergence. Based on a Fr…
In this work, we studied the problem of enhancing supervised learning with fairness requirements. We presented a framework based on empirical risk minimization under a novel and generalized fairness constraint. Contrarily to the previous methods, ou…
We tackle the problem of algorithmic fairness, where the goal is to avoid the unfairly influence of sensitive information, in the general context of …
In a system of three stochastic variables, the Partial Information Decomposition (PID) of Williams and Beer dissects the information that two variabl…
Impedance control is a well-established technique to control interaction forces in robotics. However, real implementations of impedance control with …
Motion planning in multi-contact scenarios has recently gathered interest within the legged robotics community, however actuator force/torque limits …
Physical interactions are inevitable part of human-robot collaboration tasks and rather than exhibiting simple reactive behaviors to human interactio…
This paper discusses online algorithms for inverse dynamics modelling in robotics. Several model classes including rigid body dynamics (RBD) models, …
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