Peterfreund, Erez Lindenbaum, Ofir Dietrich, Felix Bertalan, Tom Gavish, Matan Kevrekidis, Ioannis G Coifman, Ronald R
Published in
Proceedings of the National Academy of Sciences of the United States of America
We propose a local conformal autoencoder (LOCA) for standardized data coordinates. LOCA is a deep learning-based method for obtaining standardized data coordinates from scientific measurements. Data observations are modeled as samples from an unknown, nonlinear deformation of an underlying Riemannian manifold, which is parametrized by a few normali...
Hales, Patrick W Pfeuffer, Josef A Clark, Chris
Published in
Journal of magnetic resonance imaging : JMRI
Arterial spin labeling (ASL) is a useful tool for measuring cerebral blood flow (CBF). However, due to the low signal-to-noise ratio (SNR) of the technique, multiple repetitions are required, which results in prolonged scan times and increased susceptibility to artifacts. To develop a deep-learning-based algorithm for simultaneous denoising and sup...
Massi, Michela Carlotta; Gasperoni, Francesca; Ieva, Francesca; Paganoni, Anna Maria; Zunino, Paolo; Manzoni, Andrea; Franco, Nicola Rares; Veldeman, Liv; Ost, Piet; Fonteyne, Valerie;
...
Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-spe...
Sewani, Harshini Kashef, Rasha
Published in
Children
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by a lack of social communication and social interaction. Autism is a mental disorder investigated by social and computational intelligence scientists utilizing advanced technologies such as machine learning models to enhance clinicians’ ability to provide robust diagnosi...
Wang, Zhen Wang, Chunyu Gao, Chao Li, Xuelong Li, Xianghua
Published in
Science China Information Sciences
Dynamic community detection is significant for controlling and capturing the temporal features of networks. The evolutionary clustering framework provides a temporal smoothness constraint for simultaneously maximizing the clustering quality at the current time step and minimizing the clustering deviation between two successive time steps. Based on ...
Amaya, Jorge; 86999; Dupuis, Romain; Innocenti, Maria Elena; 62745; Lapenta, Giovanni; 52182;
status: published
mikuš, michael
Kvalitní data jsou zásadní pro důvěryhodná rozhodnutí na datech založená. Značná část současných přístupů k měření kvality dat je spojena s náročnou, odbornou a časově náročnou prací, která vyžaduje manuální přístup k dosažení odpovídajících výsledků. Tyto přístupy jsou navíc náchylné k chybám a nevyužívají plně potenciál umělé inteligence (AI). Mo...
Solinas, Miguel Galiez, Clovis cohendet, romain Rousset, Stéphane Reyboz, Marina Mermillod, Martial
Generative autoencoders are designed to model a target distribution with the aim of generating samples and it has also been shown that specific non-generative autoencoders (i.e. contractive and denoising autoencoders) can be turned into gen-erative models using reinjections (i.e. iterative sampling). In this work, we provide mathematical evidence t...
Wang, Chenguang Tindemans, Simon Pan, Kaikai Palensky, Peter
State estimation is of considerable significance for the power system operation and control. However, well-designed false data injection attacks can utilize blind spots in conventional residual-based bad data detection methods to manipulate measurements in a coordinated manner and thus affect the secure operation and economic dispatch of grids. In ...
Liang, Ying Wang, Haifeng Yang, Jialiang Li, Xiong Dai, Chan Shao, Peng Tian, Geng Wang, Bo Wang, Yinglong
Published in
Frontiers in Bioengineering and Biotechnology
Cancer of unknown primary site (CUPS) is a type of metastatic tumor for which the sites of tumor origin cannot be determined. Precise diagnosis of the tissue origin for metastatic CUPS is crucial for developing treatment schemes to improve patient prognosis. Recently, there have been many studies using various cancer biomarkers to predict the tissu...
