Publications associées à Hand-Object Interaction: From Human Demonstrations to Robot Manipulation

Publications associées (17)

Behaviour Range Optimization of the Dexterous Robotic Open Parametric Hand

Josephine Anna Eleanor Hughes, Kieran Daniel Gilday, Robin Carlet

Embodied intelligence could grant soft, robotic manipulators with increased performance in adaptability and dexterity. However, we currently have a lack of tools for the forward design of finger behaviours with high-dimensional morphology. We take an open- ...

IEEE2025

Learning Hand State Estimation for a Light Exoskeleton

Luca Randazzo

We propose a machine learning-based estimator of the hand state for rehabilitation purposes, using light exoskeletons. These devices are easy to use and useful for delivering domestic and frequent therapies. We build a supervised approach using information ...

Springer Nature2025

Masked Diffusion Strategy for Privacy-Preserving Distributed Learning

Ali H. Sayed

To protect both local gradients and estimated parameters in distributed learning, this paper introduces a masked diffusion (MD) strategy, leading to two algorithms: the MD stochastic gradient (MD-SG) and the MD primal-dual stochastic gradient (MPD-SG). The ...

2025

Ion Sieving in Two-Dimensional Membranes from First Principles

Nicola Marzari, Nicéphore Arthur François Bonnet

A first-principles approach for calculating ion separation in solution through two-dimensional (2D) membranes is proposed and applied. Ionic energy profiles across the membrane are obtained first, where solvation effects are simulated explicitly with machi ...

2025

Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities

Michaël Unser, Rahul Parhi

We investigate the function-space optimality (specifically, the Banach-space optimality) of a large class of shallow neural architectures with multivariate nonlinearities/activation functions. To that end, we construct a new family of Banach spaces defined ...

SIAM PUBLICATIONS2025

Rehabilitation exoskeleton system with bidirectional virtual reality feedback training strategy

Rui Wu

Virtual reality (VR) technology revitalises rehabilitation training by creating rich, interactive virtual rehabilitation scenes and tasks that deeply engage patients. Robotics with immersive VR environments have the potential to significantly enhance the s ...

2024

Teachers, Take Care of the Essential. the Rest Is Story: Using LLM and Social Robots for Content Approaching by Storytelling

Anne-Marie Rusu, Daniel Carnieto Tozadore

Social robots are widely used for educational activities, especially to attract children's attention. As a side effect, pupils' excitement can suppress their focus on the tutors and the content being approached. A potential solution to tackle this issue is ...

IEEE Computer Society2024

How Two-Layer Neural Networks Learn, One (Giant) Step at a Time

Florent Gérard Krzakala, Bruno Loureiro, Ludovic Théo Stephan, Yatin Dandi, Luca Pesce

For high-dimensional Gaussian data, we investigate theoretically how the features of a two-layer neural network adapt to the structure of the target function through a few large batch gradient descent steps, leading to an improvement in the approximation c ...

2024

Aerial Tensile Perching and Disentangling Mechanism for Long-Term Environmental Monitoring

Mirko Kovac

Aerial robots show significant potential for forest canopy research and environmental monitoring by providing data collection capabilities at high spatial and temporal resolutions. However, limited flight endurance hinders their application. Inspired by na ...

Institute of Electrical and Electronics Engineers Inc.2024

Inverse Graph Learning from Social Interactions

Valentina Shumovskaia

The social learning paradigm for distributed hypothesis testing involves a collection of agents interacting over a graph, each observing streaming data that provide evidence about the state of the environment. These agents perform a series of local Bayesia ...

EPFL2024

Euclid preparation XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong-lensing events

Frédéric Courbin, Georges Meylan, Georgios Vernardos, Benjamin Yvan Alexandre Clement

Forthcoming imaging surveys will increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of billions of galaxies will have to be inspected to identify potential candidates. In this context, deep-le ...

Edp Sciences S A2024

A qualitative AI security risk assessment of autonomous vehicles

Alexandre Massoud Alahi, Kathrin Grosse

This paper systematically analyzes the security risks associated with artificial intelligence (AI) components in autonomous vehicles (AVs). Given the increasing reliance on AI for various AV functions, from perception to control, the potential for security ...

Elsevier BV2024

Simultaneous Quantification of Multiple Drugs by Machine Learning on Electrochemical Sensors

Sandro Carrara, Lin Du, Tatsunori Matsumoto

Electrochemical devices and systems are significant for the development of therapeutic drug monitoring (TDM) and personalized therapy. However, electrochemical sensors are usually not that much selective. Therefore, innovative machine learning (ML) approac ...

Institute of Electrical and Electronics Engineers Inc.2024

A PAC-Bayesian Framework for Optimal Control with Stability Guarantees

Mahrokh Ghoddousiboroujeni, Giancarlo Ferrari Trecate, Clara Lucía Galimberti

Stochastic Nonlinear Optimal Control (SNOC) involves minimizing a cost function that averages out the random uncertainties affecting the dynamics of nonlinear systems. For tractability reasons, this problem is typically addressed by minimizing an empirical ...

IEEE2024

How can LLMs transform the robotic design process?

Josephine Anna Eleanor Hughes, Francesco Stella

NATURE PORTFOLIO2023

CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks

Antoine Bosselut, Syrielle Mathilde Marie Montariol, Debjit Paul, Mahammad Ismayilzada

Recent efforts in natural language processing (NLP) commonsense reasoning research have yielded a considerable number of new datasets and benchmarks. However, most of these datasets formulate commonsense reasoning challenges in artificial scenarios that ar ...

Association for Computational Linguistics (ACL)2023

HyperMixer: An MLP-based Low Cost Alternative to Transformers

Fabio James Fehr, François Fleuret, Arnaud Pannatier, Haolin Chen

Transformer-based architectures are the model of choice for natural language understanding, but they come at a significant cost, as they have quadratic complexity in the input length, require a lot of training data, and can be difficult to tune. In the pur ...

Assoc Computational Linguistics-Acl2023