Motility as a tool to uncover mobility practices

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The growing popularity of virtual reality systems has led to a renewed interest in understanding the neurophysiological correlates of the illusion of self-motion (vection), a phenomenon that can be both intentionally induced or avoided in such systems, dep ...

Sometimes treatment effects are absent in a subgroup of the population. For example, penicillin has no effect on severe symptoms in individuals infected by resistant Staphylococcus aureus, and codeine has no effect on pain in individuals with certain polym ...

A critical role of online platforms like Facebook, Wikipedia, YouTube, Amazon, Doordash, and Tinder is to moderate content. Interventions like banning users or deleting comments are carried out thousands of times daily and can potentially improve our onlin ...

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, ...

Online platforms have banned ("deplatformed") influencers, communities, and even entire websites to reduce content deemed harmful. Deplatformed users often migrate to alternative platforms, which raises concerns about the effectiveness of deplatforming. He ...

Moving from association to causal analysis of neuroimaging data is crucial to advance our understanding of brain function. The arrow-of-time (AoT), that is, the known asymmetric nature of the passage of time, is the bedrock of causal structures shaping phy ...

Functional and structural connectivity alterations in short- and long-range projections have been reported across neurodevelopmental disorders (NDD). Interhemispheric callosal projection neurons (CPN) represent one of the major long-range projections in th ...

Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports injuries in ath ...

Many real‐life treatments are of limited supply and cannot be provided to all individuals in the population. For example, patients on the liver transplant waiting list usually cannot be assigned a liver transplant immediately at the time they reach highest ...

The presence of competing events, such as death, makes it challenging to define causal effects on recurrent outcomes. In this thesis, I formalize causal inference for recurrent events, with and without competing events. I define several causal estimands an ...

Models trained with counterfactually augmented data learn representations of the causal structure of tasks, enabling robust generalization. However, high-quality counterfactual data is scarce for most tasks and not easily generated at scale. When crowdsour ...

We propose ordering-based approaches for learning the maximal ancestral graph (MAG) of a structural equation model (SEM) up to its Markov equivalence class (MEC) in the presence of unobserved variables. Existing ordering-based methods in the literature rec ...

Confounding variables are a recurrent challenge for causal discovery and inference. In many situations, complex causal mechanisms only manifest themselves in extreme events, or take simpler forms in the extremes. Stimulated by data on extreme river flows a ...

Pearl's do calculus is a complete axiomatic approach to learn the identifiable causal effects from observational data. When such an effect is not identifiable, it is necessary to perform a collection of often costly interventions in the system to learn the ...

The shear stiffness of headed stud connector is a critical parameter for the calculation of deflection and inter-facial shear force for steel-concrete composite structure. Thus, this study presented a promising data-driven model auto-tuning Deep Forest (AT ...

This paper analyzes efficiency and profitability in the Swiss banking sector over the period 1997–2019. We find strong evidence for scale economies: for most banks in the sample, efficiency and profitability increase with bank size. Using an instrumental v ...

Human nutrition and dietary habits shape our health, daily life, societies, the environment, and life on earth in general. However, it remains challenging to understand and attempt to change dietary behaviors using traditional methods due to measurement an ...

One of the main goal of Artificial Intelligence is to develop models capable of providing valuable predictions in real-world environments. In particular, Machine Learning (ML) seeks to design such models by learning from examples coming from this same envi ...

This research explores the unreasoned influences of locational behaviour – i.e. locational habits – in Activity- Travel-Behaviour (ATB). In particular, the interrelations between Activity Space characteristics and mobility patterns. In a wider research eff ...

Observational studies reporting on adjusted associations between childhood body mass index (BMI; weight (kg)/height (m)(2)) rebound and subsequent cardiometabolic outcomes have often not paid explicit attention to causal inference, including definition of ...

Motility as a tool to uncover mobility practices

Chattez avec Graph Search

Modulation of Visually Induced Self-motion Illusions by α Transcranial Electric Stimulation over the Superior Parietal Cortex

Using Negative Control Populations to Assess Unmeasured Confounding and Direct Effects

Content Moderation in Online Platforms

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Deplatforming did not decrease Parler users' activity on fringe social media

The arrow-of-time in neuroimaging time series identifies causal triggers of brain function

CDKL5 sculpts functional callosal connectivity to promote cognitive flexibility

Causal inference with recurrent and competing events

Longitudinal incremental propensity score interventions for limited resource settings

Interventionist estimands in event history analysis

DISCO: Distilling Counterfactuals with Large Language Models

Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables

Causal modelling of heavy-tailed variables and confounders with application to river flow

Minimum Cost Intervention Design for Causal Effect Identification

Auto-tuning deep forest for shear stiffness prediction of headed stud connectors

Scale effects on efficiency and profitability in the Swiss banking sector

Computational Approaches for Studying Dietary Behaviors with Digital Traces

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Home, Spatial Familiarity And Routines In Mobility Behaviours

Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound