iCub Joint Space Self-Collision Avoidance [Data & Code]

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On the use of applied machine learning and digital infrastructure to leverage social media data in health and epidemiology

Martin Mathias Müller

The quantification of population-level health behaviors is crucial for guiding public health policy. However, traditional methods for measuring such health behaviors have several short- comings. In recent years social media data has been successfully used ...

EPFL2021

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Silvestro Micera, Fiorenzo Artoni, Vincent Alexandre Mendez, Leonardo Pollina

The control of robotic prosthetic hands (RPHs) for upper limb amputees is far from optimal. Simultaneous and proportional finger control of a RPH based on EMG signals is still challenging. Based on EMG and kinematics recordings of subjects following a pre- ...

IEEE2021

Does spontaneous motion lead to intuitive Body-Machine Interfaces? A fitness study of different body segments for wearable telerobotics

Dario Floreano, Fabrizio Schiano, Matteo Macchini

Human-Robot Interfaces (HRIs) represent a crucial component in telerobotic systems. Body-Machine Interfaces (BoMIs) based on body motion can feel more intuitive than standard HRIs for naive users as they leverage humans’ natural control capability over the ...

2021

Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search

Mathieu Salzmann, Kaicheng Yu

Weight sharing has become a de facto standard in neural architecture search because it enables the search to be done on commodity hardware. However, recent works have empirically shown a ranking disorder between the performance of stand-alone architectures ...

IEEE COMPUTER SOC2021

Introducing reinforcement learning to the energy system design process

Jean-Louis Scartezzini, Amarasinghage Tharindu Dasun Perera, Vahid Moussavi Nik, Pamuditha Udaranga Wickramasinghe

Design optimization of distributed energy systems has become an interest of a wider group of researchers due the capability of these systems to integrate non-dispatchable renewable energy technologies such as solar PV and wind. White box models, using line ...

2020

Disentangling feature and lazy training in deep neural networks

Matthieu Wyart, Mario Geiger, Stefano Spigler, Arthur Ulysse Jacot-Guillarmod

Two distinct limits for deep learning have been derived as the network width h -> infinity, depending on how the weights of the last layer scale with h. In the neural tangent Kernel (NTK) limit, the dynamics becomes linear in the weights and is described b ...

IOP PUBLISHING LTD2020

Characterising Structure and Stability of Materials using Machine Learning

Andrea Anelli

The search of novel materials using in-silico high-throughput screening is emerging as a fundamental step in the pipeline of materials discovery, but its low yields in terms of synthesisable structures limit its effectiveness. In order to isolate configura ...

EPFL2020

From Modular Origami Robots to Polygon-based Modular Systems: a New Paradigm in Reconfigurable Robotics

Christoph Heinrich Belke

A useful robot is one that fulfils its intended function. In a factory setting, where robots have been used successfully for decades, this function is often singular and clearly defined. Similarly, the surroundings of the robot are mostly known, sterile, a ...

EPFL2020