Articles with "hierarchical graph" as a keyword



Transformer based models with hierarchical graph representations for enhanced climate forecasting

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Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-07897-4

Abstract: Accurate climate predictions are essential for agriculture, urban planning, and disaster management. Traditional forecasting methods often struggle with regional accuracy, computational demands, and scalability. This study proposes a Transformer-based deep learning model for daily temperature… read more here.

Keywords: climate; transformer based; forecasting; graph ... See more keywords

Map-Adaptive Multimodal Trajectory Prediction Using Hierarchical Graph Neural Networks

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Published in 2023 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2023.3270739

Abstract: Predicting the multimodal future motions of neighboring agents is essential for an autonomous vehicle to navigate complex scenarios. It is challenging as the motion of an agent is affected by the complex interaction among itself,… read more here.

Keywords: map adaptive; future motions; hierarchical graph; graph ... See more keywords

Toward Mobile Palmprint Recognition via Multi-View Hierarchical Graph Learning

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Published in 2025 at "IEEE Transactions on Information Forensics and Security"

DOI: 10.1109/tifs.2024.3497805

Abstract: Three significant challenges have been limiting the stable palmprint recognition via mobile devices: 1) rotations and unconsensus scales of the unconstrait hand; 2) noises generated in the open imaging environments; and 3) low quality images… read more here.

Keywords: recognition; palmprint recognition; multi view; palmprint ... See more keywords

Hierarchical Graph Augmented Deep Collaborative Dictionary Learning for Classification

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Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"

DOI: 10.1109/tits.2022.3177647

Abstract: Recently, deep dictionary learning (DDL) has aroused attention due to its abilities of learning multiple different dictionaries and extracting multi-level abstract feature representations for samples. It has been applied to many intelligent recognition tasks, such… read more here.

Keywords: hierarchical graph; dictionary learning; deep collaborative; collaborative dictionary ... See more keywords

A Structure-aware Hierarchical Graph-based Multiple Instance Learning Framework for pT Staging in Histopathological Image.

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Published in 2023 at "IEEE transactions on medical imaging"

DOI: 10.1109/tmi.2023.3273236

Abstract: Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to surrounding tissues, which relates to the prognosis and treatment choices. The pT staging relies on the field-of-views from multiple magnifications… read more here.

Keywords: structure aware; hierarchical graph; instance learning; graph based ... See more keywords

Semi-Supervised Hierarchical Graph Classification

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Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"

DOI: 10.1109/tpami.2022.3203703

Abstract: Node classification and graph classification are two graph learning problems that predict the class label of a node and the class label of a graph respectively. A node of a graph usually represents a real-world… read more here.

Keywords: network; semi supervised; graph; hierarchical graph ... See more keywords

Tooth Alignment Network Based on Landmark Constraints and Hierarchical Graph Structure.

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Published in 2022 at "IEEE transactions on visualization and computer graphics"

DOI: 10.1109/tvcg.2022.3218028

Abstract: Automatic tooth alignment target prediction is vital in shortening the planning time of orthodontic treatments and aligner designs. Generally, the quality of alignment targets greatly depends on the experience and ability of dentists and has… read more here.

Keywords: hierarchical graph; network; landmark constraints; tooth alignment ... See more keywords

Learning Physics with a Hierarchical Graph Network

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Published in 2022 at "Computer Graphics Forum"

DOI: 10.1111/cgf.14643

Abstract: We propose a hierarchical graph for learning physics and a novel way to handle obstacles. The finest level of the graph consist of the particles itself. Coarser levels consist of the cells of sparse grids… read more here.

Keywords: physics hierarchical; network; physics; learning physics ... See more keywords
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Hierarchical Graph Representation of Pharmacophore Models

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Published in 2020 at "Frontiers in Molecular Biosciences"

DOI: 10.3389/fmolb.2020.599059

Abstract: For the investigation of protein-ligand interaction patterns, the current accessibility of a wide variety of sampling methods allows quick access to large-scale data. The main example is the intensive use of molecular dynamics simulations applied… read more here.

Keywords: representation pharmacophore; graph representation; hierarchical graph; pharmacophore models ... See more keywords

BHGAttN: A Feature-Enhanced Hierarchical Graph Attention Network for Sentiment Analysis

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Published in 2022 at "Entropy"

DOI: 10.3390/e24111691

Abstract: Recently, with the rise of deep learning, text classification techniques have developed rapidly. However, the existing work usually takes the entire text as the modeling object and pays less attention to the hierarchical structure within… read more here.

Keywords: attention network; graph; hierarchical graph; attention ... See more keywords