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Deep motion forecasting models have achieved great success when trained on a massive amount of data. Yet, they often perform poorly when training data is limited. To address this challenge, we propose a transfer learning approach for efficiently adapting p ...
The lack of knowledge regarding air entrainment caused by large jets in hydraulic structures, such as downstream Pelton turbines, has led EDF (Electricité de France) to carry out a test series to optimize the La Coche Power plant. The data extracted from t ...
The concerns for climate change and the transition to renewables is increasing the relevance of superconducting applications: High Temperature Superconductor (HTS) cables for efficient power transmission, superconducting magnets for nuclear fusion, superco ...
Participatory sensing has become a new data collection paradigm that leverages the wisdom of the crowd for big data applications without spending cost to buy dedicated sensors. It collects data from human sensors by using their own devices such as cell pho ...
We introduce the framework of reality-assisted evolution to summarize a growing trend towards combining model-based and model-free approaches to improve the design of physically embodied soft robots. In silico, data-driven models build, adapt, and improve ...
The initial goal of this project was to determine by experimenting on a chip that where already design the ideal parameters for the dielectrophoresis of single walled carbon nanotubes. The epidemic blocking the access to the lab, the subject evolved to foc ...
Human trajectory forecasting in crowds, at its core, is a sequence prediction problem with specific challenges of capturing inter-sequence dependencies (social interactions) and consequently predicting socially-compliant multimodal distributions. In recent ...
Developing robots that can contribute to cleaning could have a significant impact on the lives of many. Cleaning wet liquid spills is a particularly challenging task for a robotic system, and has several high impact applications. This is a hard task to phy ...
Springer Science and Business Media Deutschland GmbH2020
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Various studies have been performed to analyze and asses the baroreflex sensitivity (BRS) in different settings. Our study aims at analyzing the BRS at rest and during different exercise stages and altitudes. Twenty-one young, healthy subjects underwent ex ...
2016
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Human trajectory forecasting in crowds presents the challenges of modelling social interactions and outputting collision-free multimodal distribution. Following the success of Social Generative Adversarial Networks (SGAN), recent works propose various GAN- ...
