Publications related to Question Answering in Conversations: Query Refinement Using Contextual and Semantic Information

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

EPFL Infoscience2024

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Edoardo Charbon, Claudio Bruschini, Andrei Ardelean, Paul Mos, Yang Lin

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

Berlin2024

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Romain Christophe Rémy Fleury, Janez Rus

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

2024

Topics in statistical physics of high-dimensional machine learning

Hugo Chao Cui

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

EPFL2024

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Jinzhi Lu, Xiaochen Zheng

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Tradition ...

Elsevier Sci Ltd2024

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Intraday solar irradiance forecasting using public cameras

Demetri Psaltis, Mario Paolone, Christophe Moser, Luisa Lambertini

With the significant increase in photovoltaic (PV) electricity generation, more attention has been given to PV power forecasting. Indeed, accurate forecasting allows power grid operators to better schedule and dispatch their assets, such as energy storage ...

Pergamon-Elsevier Science Ltd2024

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Martin Jaggi, Vinitra Swamy, Jibril Albachir Frej, Julian Thomas Blackwell

Interpretability for neural networks is a trade-off between three key requirements: 1) faithfulness of the explanation (i.e., how perfectly it explains the prediction), 2) understandability of the explanation by humans, and 3) model performance. Most exist ...

2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence.Althou ...

EPFL2024

Machine Learning for Modeling Stock Returns

Teng Andrea Xu

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

EPFL2024

Question Answering in Conversations: Query Refinement Using Contextual and Semantic Information

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Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Topics in statistical physics of high-dimensional machine learning

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Intraday solar irradiance forecasting using public cameras

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Machine Learning for Modeling Stock Returns

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Topics in statistical physics of high-dimensional machine learning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Intraday solar irradiance forecasting using public cameras

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Machine Learning for Modeling Stock Returns