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Concept

Language acquisition

Related publications (30)

BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables

David Atienza Alonso, Miguel Peon Quiros, Pasquale Davide Schiavone, Rubén Rodríguez Álvarez, Denisa-Andreea Constantinescu, Stefano Albini, Dimitrios Samakovlis

The design of low-power wearables for the biomedical domain has received a lot of attention in recent decades, as technological advances in chip manufacturing have allowed real-time monitoring of patients using low-complexity ML within the mW range. Despit ...

Institute of Electrical and Electronics Engineers (IEEE)2024

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization

Patrick Thiran, Anthony Damien Jonathan Bardou

Bayesian Optimization (BO) is typically used to optimize an unknown function f that is noisy and costly to evaluate, by exploiting an acquisition function that must be maximized at each optimization step. Even if provably asymptotically optimal BO algorith ...

2024

Driving and suppressing the human language network using large language models

Martin Schrimpf

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

Nature Portfolio2024

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Muhamed Barakovic, Marco Pizzolato

Purpose: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approac ...

Wiley2024

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Devis Tuia, Marc Conrad Russwurm, Thiên-Anh Claris Nguyen, Gaston Jean Lenczner

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Elsevier Science Inc2024

Robust gamma-aminobutyric acid and energy metabolism measurements by proton and phosphorus magnetic resonance spectroscopy and fingerprinting

Songi Lim

Magnetic resonance spectroscopy (MRS) is the only technique that can detect endogenous metabolites directly and non-invasively in vivo. It allows to identify different metabolites and analyze the dynamic neurochemical processes in the brain, skeletal muscl ...

EPFL2023

BLACK-BOX ATTACKS ON IMAGE ACTIVITY PREDICTION AND ITS NATURAL LANGUAGE EXPLANATIONS

Andrea Cavallaro

Explainable AI (XAI) methods aim to describe the decision process of deep neural networks. Early XAI methods produced visual explanations, whereas more recent techniques generate multimodal explanations that include textual information and visual represent ...

Ieee Computer Soc2023

Language Learning using Caption Generation within Reciprocal Multi-Party Child-Tutor-Tutee Interaction

Barbara Bruno

Reciprocal Peer Tutoring (RPT) is a learning paradigm characteristic of collaborative interaction between learners with alternating tutortutee roles. In recent years, robot-assisted language learning (RALL) has gained traction by its wide application for l ...

ASSOC COMPUTING MACHINERY2023

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Gulnaz Ganeeva

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

EPFL2023

Towards Novel Evaluation Methods for Social Dialog Systems

Ekaterina Svikhnushina

Language has shaped human evolution and led to the desire to endow machines with language abilities. Recent advancements in natural language processing enable us to achieve this breakthrough in human-machine interaction. However, introducing conversational ...

EPFL2023

Early motor skill acquisition in healthy older adults: brain correlates of the learning process

Friedhelm Christoph Hummel, Takuya Morishita, Chang-Hyun Park, Pablo Maceira Elvira, Manon Chloé Durand-Ruel, Maeva Moyne

Motor skill learning is a crucial process at all ages. However, healthy aging is often accompanied by a reduction in motor learning capabilities. This study characterized the brain dynamics of healthy older adults during motor skill acquisition and identif ...

OXFORD UNIV PRESS INC2023

Type-Preserving Compilation of Class-Based Languages

Guillaume André Fradji Martres

The Dependent Object Type (DOT) calculus was designed to put Scala on a sound basis, but while DOT relies on structural subtyping, Scala is a fundamentally class-based language. This impedance mismatch means that a proof of DOT soundness by itself is ...

EPFL2023

QuNex-An integrative platform for reproducible neuroimaging analytics

Valerio Zerbi

IntroductionNeuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in ...

FRONTIERS MEDIA SA2023

Dataset for manuscript: Rock anisotropy promotes hydraulic fracture containment at depth

Brice Tanguy Alphonse Lecampion, Carlo Peruzzo, Seyyedmaalek Momeni, Guanyi Lu, Fatima-Ezzahra Moukhtari

This is the experimental data used in manuscript: "Rock anisotropy promotes hydraulic fracture containment at depth". This data set has 5 folders: K1, T2, M3 and M4 contain the raw data collected by active acoustic monitoring system and various pumps and t ...

EPFL Infoscience2023

Improving time-resolution and sensitivity of in situ X-ray photoelectron spectroscopy of a powder catalyst by modulated excitation

Oliver Kröcher, Davide Ferri, Filippo Buttignol

Ambient pressure X-ray photoelectron spectroscopy (APXPS) is a powerful tool to characterize the surface structure of heterogeneous catalysts in situ. In order to improve the time resolution and the signal-to-noise (S/N) ratio of photoemission spectra, we ...

ROYAL SOC CHEMISTRY2023

Empathetic Conversational Agents for Distress Support

Kalpani Anuradha Welivita

Due to the increasing demands of today's fast-paced world, mental health concerns are on the rise, which necessitates innovative approaches to provide support to those in need. Open-domain conversational agents known as chatbots, offer a unique opportunit ...

EPFL2023

Cancer hallmarks intersect with neuroscience in the tumor microenvironment

Douglas Hanahan

The mechanisms underlying the multistep process of tumorigenesis can be distilled into a logical framework involving the acquisition of functional capabilities, the so-called hallmarks of cancer, which are collectively envisaged to be necessary for maligna ...

CELL PRESS2023

Advancing Glycan Analysis: Cryogenic Ion Spectroscopy for Database-Driven Identification

Ali H Abikhodr

Glycans play a pivotal role in both physiological processes; however, the field of glycobiology remains relatively understudied within biochemistry. The intricate complexity of glycans, coupled with their abundance of isomeric forms, presents formidable ch ...

EPFL2023

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Tobias Kober, Davide Piccini

Purpose: To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-enco ...

Wiley2023

An Error-Based Approximation Sensing Circuit for Event-Triggered Low-Power Wearable Sensors

David Atienza Alonso, Alexandre Sébastien Julien Levisse, Tomas Teijeiro Campo, Flavio Ponzina, Silvio Zanoli

Event-based sensors have the potential to optimize energy consumption at every stage in the signal processing pipeline, including data acquisition, transmission, processing, and storage. However, almost all state-of-the-art systems are still built upon th ...

2023