Publications related to SleepPic. Hardware Developments for a Wearable On-line Sleep and Wake Discrimination System

Discrete choice modeling in the era of big data

The technological advancements of the past decades have allowed transforming an increasing part of our daily actions and decisions into storable data, leading to a radical change in the scale and scope of available data in relation to virtually any object ...

EPFL2024

Adding Color to Mass Spectra of Biopolymers: Charge Determination Analysis (CHARDA) Assigns Charge State to Every Ion Peak

Yury Tsybin, Natalia Gasilova, Laure Menin, Anton Kozhinov, Konstantin Nagornov

Traditionally, mass spectrometry (MS) output is the ion abundance plotted versus the ionic mass-to-charge ratio m/z. While employing only commercially available equipment, Charge Determination Analysis (CHARDA) adds a third dimension to MS, estimating for ...

Amer Chemical Soc2024

SVGC-AVA: 360-Degree Video Saliency Prediction With Spherical Vector-Based Graph Convolution and Audio-Visual Attention

Pascal Frossard, Chenglin Li, Li Wei, Qin Yang, Yuelei Li

Viewers of 360-degree videos are provided with both visual modality to characterize their surrounding views and audio modality to indicate the sound direction. Though both modalities are important for saliency prediction, little work has been done by joint ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

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

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

EPFL Infoscience2024

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Wenlong Liao, Yi Zhang, Zhe Yang

Recently, remarkable progress has been made in the application of machine learning (ML) techniques (e.g., neural networks) to transformer fault diagnosis. However, the diagnostic processes employed by these techniques often suffer from a lack of interpreta ...

Piscataway2024

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

Michele Ceriotti, Federico Grasselli

The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)he ...

Amer Physical Soc2024

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

Optimizing Dynamic Aperture Studies with Active Learning

Tatiana Pieloni, Ekaterina Krymova, Davide Di Croce, Massimo Giovannozzi

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

2024

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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Volkan Cevher, Grigorios Chrysos, Fanghui Liu

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

SleepPic. Hardware Developments for a Wearable On-line Sleep and Wake Discrimination System

Graph Chatbot

Chat with Graph Search

Discrete choice modeling in the era of big data

Adding Color to Mass Spectra of Biopolymers: Charge Determination Analysis (CHARDA) Assigns Charge State to Every Ion Peak

SVGC-AVA: 360-Degree Video Saliency Prediction With Spherical Vector-Based Graph Convolution and Audio-Visual Attention

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Optimizing Dynamic Aperture Studies with Active Learning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Adding Color to Mass Spectra of Biopolymers: Charge Determination Analysis (CHARDA) Assigns Charge State to Every Ion Peak

SVGC-AVA: 360-Degree Video Saliency Prediction With Spherical Vector-Based Graph Convolution and Audio-Visual Attention

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Optimizing Dynamic Aperture Studies with Active Learning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Discrete choice modeling in the era of big data

Generalization of Scaled Deep ResNets in the Mean-Field Regime