Results 31 to 40 of about 69,930 (266)

Spatio-Temporal Graph Convolutional Network Incorporating Knowledge Graph Embeddings for Hydrological Time Series Prediction

IEEE Access
This paper proposes a spatio-temporal graph convolutional network incorporating knowledge graph embeddings for hydrological time series prediction. A knowledge graph is constructed to integrate the spatio-temporal features of hydrological monitoring ...
Xin Jin, Mengyuan Qin, Hao Duan
doaj   +1 more source

Selective Temporal Knowledge Graph Reasoning

Proceedings of the Language Resources and Evaluation Conference
Temporal Knowledge Graph (TKG), which characterizes temporally evolving facts in the form of (subject, relation, object, timestamp), has attracted much attention recently. TKG reasoning aims to predict future facts based on given historical ones. However, existing TKG reasoning models are unable to abstain from predictions they are uncertain, which ...
Zhongni Hou, Xiaolong Jin 0001, Zixuan Li 0001, Long Bai 0002, Jiafeng Guo, Xueqi Cheng   +5 more
openaire   +3 more sources

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas F. Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

Summarizing Entity Temporal Evolution in Knowledge Graphs [PDF]

Companion Proceedings of The 2019 World Wide Web Conference, 2019
Companion Proceedings of The 2019 World Wide Web Conference on - WWW '19 The 2019 World Wide Web Conference, WWW '19, San Francisco, USA, 13 May 2019 - 17 May 2019; New York, NY : ACM Press 961-965 (2019).
Mayesha Tasnim, Diego Collarana, Damien Graux, Fabrizio Orlandi, Maria-Esther Vidal   +4 more
openaire   +3 more sources

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

FEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source

Temporal Graph Neural Networks for Modeling Student Knowledge Evolution and Predicting Learning Trajectories

Algorithms
Accurately modeling student knowledge evolution is a central challenge in personalized learning and adaptive educational systems. Traditional sequential or static approaches often fail to capture both the temporal dynamics of learning and the relational ...
Deborah Olaniyan, Ruth Wario
doaj   +1 more source

One-shot Learning for Temporal Knowledge Graphs

CoRR, 2020
Most real-world knowledge graphs are characterized by a long-tail relation frequency distribution where a significant fraction of relations occurs only a handful of times. This observation has given rise to recent interest in low-shot learning methods that are able to generalize from only a few examples.
Mehrnoosh Mirtaheri, Mohammad Rostami, Xiang Ren 0001, Fred Morstatter, Aram Galstyan   +4 more
openaire   +2 more sources

Baseline Regional Cholinergic Denervation Predicts Cognitive Trajectories in Moderate Parkinson Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown, Giulia Carli, Prabesh Kanel, Stiven Roytman, Jaimie Barr, Nicolaas I. Bohnen, Roger L. Albin   +6 more
wiley   +1 more source

Enhanced Temporal Knowledge Graph Completion via Learning High-Order Connectivity and Attribute Information

Applied Sciences, 2023
Temporal knowledge graph completion (TKGC) refers to the prediction and filling in of missing facts on time series, which is essential for many downstream applications.
Minwei Wen, Hongyan Mei, Wei Wang, Xing Zhang   +3 more
doaj   +1 more source

Temporal graph memory networks for knowledge tracing

Knowledge and Information Systems
Abstract Tracing a student's knowledge growth given the past exercise answering is a vital objective in automatic tutoring systems to customize the learning experience. Yet, achieving this objective is a non-trivial task as it involves modeling the knowledge state across multiple knowledge components (KCs) while considering their ...
Seif Gad, Sherif M. Abdelfattah, Ghodai M. Abdelrahman   +2 more
openaire   +2 more sources