Publications associées à Randomized experiment

Biases in Information Selection and Processing: Survey Evidence from the Pandemic

We conduct two survey experiments to study which information people choose to consume and how it affects their beliefs. In the first experiment, respondents choose between optimistic and pessimistic article headlines related to the COVID-19 pandemic and ar ...

2024

Reversible photo-electrochemical device for solar hydrogen and power generation

Sophia Haussener, Saurabh Yuvraj Tembhurne, Alexandre Dominique M. Cattry, Matthieu Jonin, Mahendra Patel

A reversible photo-electrochemical device operating under concentrated irradiation could offer a stand-alone solution for producing solar fuel (in photo-driven electrolysis mode) and power (in fuel cell mode). This strategy would present the advantage of h ...

2024

A FEM modelling workflow to simulate THM effects in the rock around nuclear waste packages

Matthias Timothee Stanislas Wojnarowicz

High-level waste, stemming from nuclear electricity generation poses significant environmental and safety concerns. Currently, high-level wastes are stored in interim facilities needing constant monitoring and waiting for a definitive solution. Deep geolog ...

EPFL2024

Linguistic effects on news headline success: Evidence from thousands of online field experiments (Registered Report)

Robert West, Kristina Gligoric

What makes written text appealing? In this registered report, we study the linguistic characteristics of news headline success using a large-scale dataset of field experiments (A/B tests) conducted on the popular website comparing multiple headline variant ...

PUBLIC LIBRARY SCIENCE2023

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Carmela González Troncoso, Bogdan Kulynych

Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomization when fitting model parameters to privacy-sensitive data (e.g., adding Ga ...

Assoc Computing Machinery2023

Survey experiments on economic expectations

Andreas Fuster

In this chapter, we discuss field experiments in surveys that are conducted with the purpose of learning about expectation formation and the link between expectations and behavior. We begin by reviewing the rationale for conducting experiments within surve ...

Academic Press2023

Prompting Large Language Models to Power Educational Chatbots

Denis Gillet, Juan Carlos Farah, Sandy Ingram, Fanny Kim-Lan Lasne

The recent rise in both popularity and performance of large language models has garnered considerable interest regarding their applicability to education. Technologies like ChatGPT, which can engage in human-like dialog, have already disrupted educational ...

Springer2023

Interventionist estimands in event history analysis

Matias Janvin

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 ...

EPFL2023

Harnessing Rule-Based Chatbots to Support Teaching Python Programming Best Practices

Denis Gillet, Juan Carlos Farah, Sandy Ingram, Adrian Christian Holzer

In recent years, the use of chatbots in education has been driven by advances in natural language processing and the increasing availability of digital education platforms. Although the added value of educational chatbots appears promising, researchers hav ...

Springer2023

Modeling tumor size dynamics based on real-world electronic health records and image data in advanced melanoma patients receiving immunotherapy

Olivier Michielin, Federico Amato, Monia Guidi, Nadia Terranova, Daniel Abler, Alexandre Wicky

The development of immune checkpoint inhibitors (ICIs) has revolutionized cancer therapy but only a fraction of patients benefits from this therapy. Model-informed drug development can be used to assess prognostic and predictive clinical factors or biomark ...

2023

Modeling local thermal responses of individuals: Validation of advanced human thermo-physiology models

Dolaana Khovalyg, Mohamad Rida

Human thermo-physiology models (HTPM) are useful tools to assess dynamic and non-uniform human thermal states. However, they are developed based on the physiological data of an average person. In this paper, we present a detailed evaluation of two sophisti ...

2023

Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning

Bogdan Kulynych

Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...

EPFL2023

Translating questions to estimands in randomized clinical trials with intercurrent events

Mats Julius Stensrud

Intercurrent (post-treatment) events occur frequently in randomized trials, and investigators often express interest in treatment effects that suitably take account of these events. Contrasts that naively condition on intercurrent events do not have a stra ...

2022

Transit Time Estimation in Catchments: Recent Developments and Future Directions

Andrea Rinaldo, Paolo Benettin, Gianluca Botter, Myungjin Kim

Water transit time is now a standard measure in catchment hydrological and ecohydrological research. The last comprehensive review of transit time modeling approaches was published 15+ years ago. But since then the field has largely expanded with new data, ...

AMER GEOPHYSICAL UNION2022

Determining crack kinematics from imaged crack patterns

Katrin Beyer, Bryan German Pantoja Rosero, Amir Rezaie, Ketson Roberto Maximiano Dos Santos

Determining the relationship between the cause of damage and the subsequent structural behavior of infrastructure systems requires an accurate characterization of the propagation of cracks, which represents the evolution of the damage state. When no inform ...

2022

Mixplorer: Scaffolding Design Space Exploration through Genetic Recombination of Multiple Peoples’ Designs to Support Novices’ Creativity

Pierre Dillenbourg, Richard Lee Davis, Kevin Gonyop Kim

The ability to consider a wide range of solutions to a design problem is a crucial skill for designers, and is a major differentiator between experts and novices. One reason for this is that novices are unaware of the full extent of the design space in whi ...

2022

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

Anthony Christopher Davison, Valérie Chavez

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 ...

SPRINGER2022

Scrambler Therapy for Chronic Pain after Burns and Its Effect on the Cerebral Pain Network: A Prospective, Double-Blinded, Randomized Controlled Trial

Chang-Hyun Park

Chronic pain is common after burn injuries, and post-burn neuropathic pain is the most important complication that is difficult to treat. Scrambler therapy (ST) is a non-invasive modality that uses patient-specific electrocutaneous nerve stimulation and is ...

MDPI2022

Bridging the gap from test rooms to field-tests for human indoor comfort studies: A critical review of the sustainability potential of living laboratories

Dusan Licina, Mengdi Kong

Occupants play a key role in determining final building energy consumption. Empirical evidence must support occupants' modelling. Experiments on human responses to Indoor Environmental Quality (IEQ) are usually performed in test rooms or as in-field monito ...

ELSEVIER2022

Single-neuron models linking electrophysiology, morphology, and transcriptomics across cortical cell types

Werner Alfons Hilda Van Geit, Anatoly Buchin

Which cell types constitute brain circuits is a fundamental question, but establishing the correspondence across cellular data modalities is challenging. Bio-realistic models allow probing cause-and-effect and linking seemingly disparate modalities. Here, ...

2022