Results 101 to 110 of about 497,808 (317)
A Deep Learning Framework for Traffic Data Imputation Considering Spatiotemporal Dependencies [PDF]
arXiv, 2023 Spatiotemporal (ST) data collected by sensors can be represented as multi-variate time series, which is a sequence of data points listed in an order of time. Despite the vast amount of useful information, the ST data usually suffer from the issue of missing or incomplete data, which also limits its applications. Imputation is one viable solution and is
arxiv
Simulating time to event prediction with spatiotemporal echocardiography deep learning
, 2021 9 pages, 5 ...
Shad, Rohan +10 more
openaire +2 more sources
A Bio‐Inspired Perspective on Materials Sustainability
Advanced Materials, EarlyView.This perspective discusses natural materials as inspiration for sustainable engineering designs and the processing of materials. First, circularity, longevity, parsimony, and activity are presented as essential material paradigms. The perspective then uses many examples of natural and technical materials to introduce principles such as oligo ...
Wolfgang Wagermaier +2 more
wiley +1 more source
Identifying multicellular spatiotemporal organization of cells with SpaceFlow
Nature Communications, 2022 A critical task in spatial transcriptomics analysis is to understand inherently spatial relationships among cells. Here, the authors present a deep learning framework to integrate spatial and transcriptional information, spatially extending pseudotime ...
Honglei Ren +3 more
doaj +1 more source
Deep Bayesian Active Learning for Accelerating Stochastic Simulation [PDF]
arXiv, 2021 Stochastic simulations such as large-scale, spatiotemporal, age-structured epidemic models are computationally expensive at fine-grained resolution. While deep surrogate models can speed up the simulations, doing so for stochastic simulations and with active learning approaches is an underexplored area.
arxiv
Machine Learning in Polymer Research
Advanced Materials, Volume 37, Issue 11, March 19, 2025.Artificial intelligence (AI) has permeated every aspect of science, including polymer research. Researchers from both fields need to collaborate to understand the challenges and opportunities of each domain. This review is therefore written by mathematicians and polymer chemists to highlight the key research questions polymer chemists aim to address ...
Wei Ge +4 more
wiley +1 more source
Sensors, 2018 Data-driven methods with multi-sensor time series data are the most promising approaches for monitoring machine health. Extracting fault-sensitive features from multi-sensor time series is a daunting task for both traditional data-driven methods and ...
Huihui Qiao +4 more
doaj +1 more source
Spatiotemporal Residual Networks for Video Action Recognition [PDF]
arXiv, 2016 Two-stream Convolutional Networks (ConvNets) have shown strong performance for human action recognition in videos. Recently, Residual Networks (ResNets) have arisen as a new technique to train extremely deep architectures. In this paper, we introduce spatiotemporal ResNets as a combination of these two approaches.
arxiv
Flexible 3D Kirigami Probes for In Vitro and In Vivo Neural Applications
Advanced Materials, EarlyView.A customizable and scalable approach to fabricate flexible 3D kirigami microelectrode arrays (MEAs) featuring up to 128 shanks, including surface and penetrating electrodes designed to interact with the 3D space of neural tissue, is presented. The 3D kirigami MEAs are successfully deployed in several neural applications, both in vitro and in vivo, and ...
Marie Jung +10 more
wiley +1 more source
Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network [PDF]
, 2021 Maryam Doborjeh +4 more
openalex +1 more source