Publications related to Early detection, warnings, weak signals and seeds of change: A turbulent domain of futures studies

Adapting Haptic Feedback for Guided Meditation

Cédric Duchene, Nicolas Henchoz, Emily Clare Groves, Romain Simon Collaud, Andreas Sonderegger, Yoann Pierre Douillet

Technology supporting meditation is a multimillion-dollar market that continues to grow. There is also strong academic interest to understand and improve the impact technology can have for the user experience of practitioners. However, little work investig ...

2023

THE PHASE TRANSITION FOR PLANAR GAUSSIAN PERCOLATION MODELS WITHOUT FKG

Alejandro Rivera

We develop techniques to study the phase transition for planar Gaussian percolation models that are not (necessarily) positively correlated. These models lack the property of positive associations (also known as the 'FKG inequality'), and hence many classi ...

Inst Mathematical Statistics-Ims2023

Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research

Nicolas Clairis

The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) is a brain area subject to many theories and debates over its function(s). Even its precise anatomical borders are subject to much controversy. In the past decades, the dmPFC/d ...

Oxford Univ Press2023

Game-theoretic Mechanisms for Eliciting Accurate Information

Boi Faltings

Artificial Intelligence often relies on information obtained from others through crowdsourcing, federated learning, or data markets. It is crucial to ensure that this data is accurate. Over the past 20 years, a variety of incentive mechanisms have been dev ...

2022

Vision-based Flocking in Aerial Robot Swarms

Fabian Maximilian Schilling

Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...

EPFL2022

Radical Alkynylations with EthynylBenziodoXolones: From Photocatalysis to Direct Excitation

Jérôme Waser, Stephanie Grace Elizabeth Amos

Ethynylbenziodoxolones (EBXs) have recently emerged as potent reagents for the alkynylation of radicals. Their combination with photocatalysis allows the synthesis of valuable alkynes at room temperature. Herein, we discuss two photomediated strategies for ...

2022

A Functional Perspective on Information Measures

Amedeo Roberto Esposito

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

EPFL2022

A smooth basis for atomistic machine learning

Michele Ceriotti, Kevin Kazuki Huguenin-Dumittan, Filippo Bigi

Machine learning frameworks based on correlations of interatomic positions begin with a discretized description of the density of other atoms in the neighborhood of each atom in the system. Symmetry considerations support the use of spherical harmonics to ...

AIP Publishing2022

Learning the Exciton Properties of Azo-dyes

Anne-Clémence Corminboeuf, Ksenia Briling, Alberto Fabrizio, Sergio Vela Llausi

The ab initio determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine l ...

AMER CHEMICAL SOC2021

Gaussian Process Regression for Materials and Molecules

Michele Ceriotti, David Mark Wilkins

We provide an introduction to Gaussian process regression (GPR) machinelearning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of in ...

AMER CHEMICAL SOC2021