20 citations · 66 across the 10 of their papers we have counts for
11 papers
Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer
Gemini Robotics Team, Abbas Abdolmaleki, Saminda Abeyruwan +169
General-purpose robots need a deep understanding of the physical world, advanced reasoning, and general and dexterous control. This report introduces the latest generation of the G…
Space-time multilevel quadrature methods and their application for cardiac electrophysiology
Seif Ben Bader, Helmut Harbrecht, Rolf Krause +3
We present a novel approach which aims at high-performance uncertainty quantification for cardiac electrophysiology simulations. Employing the monodomain equation to model the tran…
Real-time Classification from Short Event-Camera Streams using Input-filtering Neural ODEs
Giorgio Giannone, Asha Anoosheh, Alessio Quaglino +3
Event-based cameras are novel, efficient sensors inspired by the human vision system, generating an asynchronous, pixel-wise stream of data. Learning from such data is generally pe…
Neural Lyapunov Model Predictive Control: Learning Safe Global Controllers from Sub-optimal Examples
Mayank Mittal, Marco Gallieri, Alessio Quaglino +2
With a growing interest in data-driven control techniques, Model Predictive Control (MPC) provides an opportunity to exploit the surplus of data reliably, particularly while taking…
Safe Interactive Model-Based Learning
Marco Gallieri, Seyed Sina Mirrazavi Salehian, Nihat Engin Toklu +4
Control applications present hard operational constraints. A violation of these can result in unsafe behavior. This paper introduces Safe Interactive Model Based Learning (SiMBL),…
Space-time multilevel Monte Carlo methods and their application to cardiac electrophysiology
Seif Ben Bader, Pietro Benedusi, Alessio Quaglino +2
We present a novel approach aimed at high-performance uncertainty quantification for time-dependent problems governed by partial differential equations. In particular, we consider…
SNODE: Spectral Discretization of Neural ODEs for System Identification
Alessio Quaglino, Marco Gallieri, Jonathan Masci +1
This paper proposes the use of spectral element methods \citep{canuto_spectral_1988} for fast and accurate training of Neural Ordinary Differential Equations (ODE-Nets; \citealp{Ch…
Smart energy models for atomistic simulations using a DFT-driven multifidelity approach
Luca Messina, Alessio Quaglino, Alexandra Goryaeva +5
The reliability of atomistic simulations depends on the quality of the underlying energy models providing the source of physical information, for instance for the calculation of mi…
High-dimensional and higher-order multifidelity Monte Carlo estimators
Alessio Quaglino, Simone Pezzuto, Rolf Krause
Multifidelity Monte Carlo methods rely on a hierarchy of possibly less accurate but statistically correlated simplified or reduced models, in order to accelerate the estimation of…
Towards a multigrid method for the minimum-cost flow problem
Alessio Quaglino, Rolf Krause
We present a first step towards a multigrid method for solving the min-cost flow problem. Specifically, we present a strategy that takes advantage of existing black-box fast iterat…
Multiscale modeling, discretization, and algorithms: a survey in biomechanics
Marco Favino, Alessio Quaglino, Sonia Pozzi +2
Multiscale models allow for the treatment of complex phenomena involving different scales, such as remodeling and growth of tissues, muscular activation, and cardiac electrophysiol…