Publications related to Unethical human experimentation

A machine learning architecture for including wave breaking in envelope-type wave models

Wave breaking is a complex physical process about which open questions remain. For some applications, it is critical to include breaking effects in phase-resolved envelope-based wave models such as the non-linear Schr & ouml;dinger. A promising approach is ...

Pergamon-Elsevier Science Ltd2024

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

Alexandre Massoud Alahi, Yuejiang Liu, Parth Ashit Kothari, Danya Li

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 ...

2022

Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting

Alexandre Massoud Alahi, Parth Ashit Kothari

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- ...

2022

Reality-assisted evolution of soft robots through large-scale physical experimentation: a review

Josephine Anna Eleanor Hughes, Simon Lukas Hauser

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 ...

MIT Press Journals2021

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

Alexandre Massoud Alahi, Parth Ashit Kothari

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 ...

2021

Real World Bayesian Optimization Using Robots to Clean Liquid Spills

Josephine Anna Eleanor Hughes, Kieran Daniel Gilday

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

Efficient User Guidance for Validating Participatory Sensing Data

Thành Tâm Nguyên

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 ...

ASSOC COMPUTING MACHINERY2019

New Tools for MOOC/MOOL to Sustain Continuity of Experimentation in Control

Denis Gillet, Christophe Salzmann, Yves Henri Philippe Piguet

The use of interactive tools combined with remote laboratories has shown to be very useful for students when offered in a MOOC. The EPFL hands-on Control MOOC enables students to switch back and forth between control and observation on a remote laboratory, ...

Elsevier2019

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Unethical human experimentation

A machine learning architecture for including wave breaking in envelope-type wave models

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting

A fibre optic and machine learning based health monitoring system for superconducting power applications in modern supergrids

Reality-assisted evolution of soft robots through large-scale physical experimentation: a review

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

Immobilization of single-walled carbon nanotubes by dielectrophoresis using a microfluidic channel

Real World Bayesian Optimization Using Robots to Clean Liquid Spills

Efficient User Guidance for Validating Participatory Sensing Data

New Tools for MOOC/MOOL to Sustain Continuity of Experimentation in Control

Graph Chatbot

Chat with Graph Search

Reality-assisted evolution of soft robots through large-scale physical experimentation: a review

Efficient User Guidance for Validating Participatory Sensing Data

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

A fibre optic and machine learning based health monitoring system for superconducting power applications in modern supergrids

Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting

Real World Bayesian Optimization Using Robots to Clean Liquid Spills

New Tools for MOOC/MOOL to Sustain Continuity of Experimentation in Control

A machine learning architecture for including wave breaking in envelope-type wave models

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

Immobilization of single-walled carbon nanotubes by dielectrophoresis using a microfluidic channel