Publications related to Artificial neural network

The 2024 Magnonics Roadmap

Dirk Grundler, Thomas Yu, Ping Che, Qi Wang, Wei Zhang, Benedetta Flebus

Magnonics is a research field that has gained an increasing interest in both the fundamental and applied sciences in recent years. This field aims to explore and functionalize collective spin excitations in magnetically ordered materials for modern informa ...

2024

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Alfio Quarteroni, Francesco Regazzoni, Luca Dede'

Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-b ...

Nature Portfolio2024

The multimodality cell segmentation challenge: toward universal solutions

Sahand Jamal Rahi, Vojislav Gligorovski, Marco Labagnara, Jun Ma, Xin Yang, Maxime Emmanuel Scheder, Yao Zhang, Bo Wang, Yixin Wang, Lin Han

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimen ...

Nature Portfolio2024

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

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Alireza Amirshahi, Farnaz Forooghifar, Saleh Baghersalimi

Integrating low-power wearable systems into routine health monitoring is an ongoing challenge. Recent advances in the computation capabilities of wearables make it possible to target complex scenarios by exploiting multiple biosignals and using high-perfor ...

2024

On the Generalization of Stochastic Gradient Descent with Momentum

Volkan Cevher, Kimon Antonakopoulos

While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...

Brookline2024

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Olga Fink, Ismail Nejjar, Mengjie Zhao

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these ...

2024

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Pierre Vandergheynst, Felix Naef, Cédric Gobet, Francesco Craighero, Mohan Vamsi Nallapareddy

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome dwell times ...

2024

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Artificial neural network

The 2024 Magnonics Roadmap

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

The multimodality cell segmentation challenge: toward universal solutions

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

Partial discharge localization in power transformer tanks using machine learning methods

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

On the Generalization of Stochastic Gradient Descent with Momentum

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Graph Chatbot

Chat with Graph Search

The 2024 Magnonics Roadmap

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

The multimodality cell segmentation challenge: toward universal solutions

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Partial discharge localization in power transformer tanks using machine learning methods

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

On the Generalization of Stochastic Gradient Descent with Momentum

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems