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Publications associées (30)

Augmenting large language models with chemistry tools

Philippe Schwaller, Oliver Tobias Schilter, Andres Camilo Marulanda Bran, Carlo Baldassari

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ...

Nature Portfolio2024

Seismic Testing of Adjacent Interacting Masonry Structures – Analysis of a Blind Prediction

Katrin Beyer, Andrea Penna, Igor Tomic

Masonry aggregates, which emerged as layouts of cities and villages became denser, make up historical centres all over the world. In these aggregates, neighbouring structures may share structural walls that are joined at the interfaces by mortar or interlo ...

Springer2024

Extensions of Peer Prediction Incentive Mechanisms

Adam Julian Richardson

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

Paolo De Los Rios, Bruno Claude Daniel Fauvet, Adélaïde Alice Mohr, Satyam Tiwari, Mathieu Rebeaud, Pierre Goloubinoff

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in ne ...

Elsevier Science Inc2024

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats

Maria del Carmen Sandi Perez, Elias Georges Gebara, Ana del Rocio Conde Moro

Social behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying cooperation can be beneficial for people suffering from pathologies with impaired social behavior. Our aim was to study the brain activit ...

Springer2024

Anthony C Davison and Igor Rodionov's contribution to the Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas

Anthony Christopher Davison, Igor Rodionov

We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form "empirical-Bernstein" CSs and ...

Oxford Univ Press2024

Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

Martin Hairer

We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

Springernature2024

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Alireza Karimi, Mert Eyuboglu, Nathan Russell Powell

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

2024

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