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Paper Citation Record · LEDGER

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks

As of 21 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2504.20744.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2504.20744 v1

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measured 44 of 44 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

44 of 44 outbound references displayed

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Outbound references

Observation db7e8f18-1ff0-40b5-9d05-6f1a9306fbeb · outbound

This paper cites This approach fully leverages b oth WFC and CFC information of emotional brain states, thereby laying a foundation for accurate emotion classification.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks This approach fully leverages b oth WFC and CFC information of emotional brain states, thereby laying a foundation for accurate emotion classification

Reference 1

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This paper cites an unresolved cited work.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Unresolved cited work

Reference 2

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Observation 88d22b41-14b4-4c5d-be21-b8ee949a64d4 · outbound

This paper cites # $ = 1 %&’()*+, -.,/0 − +,$-.,/02 / 1 % ∈ , , , , -20 where !.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks # $ = 1 %&’()*+, -.,/0 − +,$-.,/02 / 1 % ∈ , , , , -20 where !

Reference 3

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Observation f40a87a0-d532-445a-abc1-f7d8d132fd92 · outbound

This paper cites EEG Source Imaging : A Practical Review of the Analysis Steps,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks EEG Source Imaging : A Practical Review of the Analysis Steps,

Reference 4

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Observation f1d830f4-6ba5-419a-bdbe-ebcfe7956149 · outbound

This paper cites Emotion Downregulation Targets Interoceptive Brain Regions While Emotion Upregulation Targets Other Af fective Brain Regions,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Emotion Downregulation Targets Interoceptive Brain Regions While Emotion Upregulation Targets Other Af fective Brain Regions,

Reference 5

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Observation f16d696b-38ea-4363-9afd-8ed914c3b16f · outbound

This paper cites The functional role of cross-frequency coupling,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks The functional role of cross-frequency coupling,

Reference 6

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DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Unresolved cited work

Reference 7

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This paper cites Low-frequency neuronal oscillations as instruments of sensory selection,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Low-frequency neuronal oscillations as instruments of sensory selection,

Reference 8

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This paper cites Alpha-band oscillations, attentio n, and controlled access to stored information,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Alpha-band oscillations, attentio n, and controlled access to stored information,

Reference 9

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Observation d658663a-cdfa-4355-a81f-83aaab77082c · outbound

This paper cites Emotion recogni tion based on group phase locking value using convolutional neural network,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Emotion recogni tion based on group phase locking value using convolutional neural network,

Reference 10

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This paper cites The Theta-Gamma Ne ural Code,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks The Theta-Gamma Ne ural Code,

Reference 11

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Observation bdeda254-a659-4991-9b86-c94f14c6769c · outbound

This paper cites EEG emotion recognition based on cross-frequency granger causality feature extraction and fusion in the left and right hemispheres,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks EEG emotion recognition based on cross-frequency granger causality feature extraction and fusion in the left and right hemispheres,

Reference 12

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Observation d0f41039-3ce3-426f-82bc-b93d6a3d02ba · outbound

This paper cites Graph Neural Network-Based EEG Classification : A Survey | IEEE Journals & Magazine | IEEE Xplore.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Graph Neural Network-Based EEG Classification : A Survey | IEEE Journals & Magazine | IEEE Xplore

Reference 13

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Observation 2f0337e0-38e5-4efa-92f3-582bbc9b9d20 · outbound

This paper cites Colloquiu m: Multiscale modeling of brain network organization,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Colloquiu m: Multiscale modeling of brain network organization,

Reference 14

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Observation 462ee96a-39e1-476a-9d37-d2e527f3de4c · outbound

This paper cites Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review,

Reference 15

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Observation 74bf02a6-b49b-4fd4-8183-06c5c3fbd3f1 · outbound

This paper cites EEG Emotion Classification Based on Graph Convolutional Network,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks EEG Emotion Classification Based on Graph Convolutional Network,

Reference 16

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Observation 39cbbac4-be55-4a09-9dd0-7075ab5d9ab9 · outbound

This paper cites EEG Emotion Recognition Based on Dynamic Graph Neural Networks,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks EEG Emotion Recognition Based on Dynamic Graph Neural Networks,

Reference 17

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Observation a7344963-a6a9-42bb-b4ac-d13baaca8b0b · outbound

This paper cites SAGN: Sp arse Adaptive Gated Graph Neural Network With Graph Regularization for Identifying Dual- View Brain Networks,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks SAGN: Sp arse Adaptive Gated Graph Neural Network With Graph Regularization for Identifying Dual- View Brain Networks,

Reference 18

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DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Unresolved cited work

Reference 19

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This paper cites Multi-Granularity Analysis of Brain Networks Assembled With Intra-Frequency and Cross-Frequency Phase Coup ling for Human EEG After Stroke,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Multi-Granularity Analysis of Brain Networks Assembled With Intra-Frequency and Cross-Frequency Phase Coup ling for Human EEG After Stroke,

Reference 21

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DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Review of Graph Neural Network in Text Classification,

Reference 22

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DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Graph Neural Networks and Their Current Applications in Bioinformatics,

Reference 23

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This paper cites Gra ph Neural Networks in Network Neuroscience,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Gra ph Neural Networks in Network Neuroscience,

Reference 24

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This paper cites EEG-Based Emo tion Recognition Using Regularized Graph Neural Networks,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks EEG-Based Emo tion Recognition Using Regularized Graph Neural Networks,

Reference 25

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DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Representation Learning with Contrastive Predictive Coding

Reference 26

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This paper cites A Graph Neur al Network for EEG- Based Emotion Recognition With Contrastive Learning and Generative Adversarial Neural Network Data Augmentation,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks A Graph Neur al Network for EEG- Based Emotion Recognition With Contrastive Learning and Generative Adversarial Neural Network Data Augmentation,

Reference 27

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Observation 7e58a3b5-b5c0-4996-bbab-85cca1ef25ec · outbound

This paper cites Emotion recognition of EEG signals based on contrastive lea rning graph convolutional model,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Emotion recognition of EEG signals based on contrastive lea rning graph convolutional model,

Reference 28

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Observation 1bb32132-89db-4d06-b4eb-084972262d1f · outbound

This paper cites On the theory of filter ampli fiers,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks On the theory of filter ampli fiers,

Reference 29

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Observation cf9babc0-daae-46f1-85ac-7eab5380bab5 · outbound

This paper cites Investigating Criti cal Frequency Bands and Channels for EEG-Based Emotion Recognition with Dee p Neural Networks,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Investigating Criti cal Frequency Bands and Channels for EEG-Based Emotion Recognition with Dee p Neural Networks,

Reference 30

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Observation abd3698d-f1b7-4c9b-a45c-7e46e7117f0f · outbound

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DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Semi-Supervised Classification with Graph Convolutional Networks

Reference 31

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This paper cites How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

Reference 32

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DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Edge Directionality Improves Lear ning on Heterophilic Graphs,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 9a5c53c1-7ac6-4530-82a5-7e5e669376d3 · outbound

This paper cites Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:25:32.683401Z digest=sha256:ea368a8a850e823b6055fbcac7b5d92f8708540ff444fd7825822b497d469ec3

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T05:25:32.688847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:25:32.688847Z digest=sha256:f05df5b15fbb4ad6a1a4d2b3e8312b46d0d24a57855af8cd26902b876a2eefbf

Observation f7b468a1-b920-424c-bc9b-4674cf9bb3a2 · outbound

This paper cites Elastic Graph Transformer Networks for EEG-Based Emotion Recognit ion,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Elastic Graph Transformer Networks for EEG-Based Emotion Recognit ion,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-16T05:25:32.694040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:25:32.694040Z digest=sha256:917d27e7f57aa991ccc4de433e1770b832ea0b0d32a2eef85557b537f9754367

Observation 125e17c9-0da6-41da-ac7a-cc6a5f90de86 · outbound

This paper cites Variational Instance-Adaptive Graph for EEG Emotion Recognition,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Variational Instance-Adaptive Graph for EEG Emotion Recognition,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T05:25:32.698943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:25:32.698943Z digest=sha256:ef7a3e19c09b8370fd277bc928bd0f353f8afead8e95aaa9b958dccb6b3368e6

Observation b3fc9ccf-57e9-4676-b28d-3eecf27b8527 · outbound

This paper cites GMSS: Graph-Based Multi-Task Se lf-Supervised Learning for EEG Emotion Recognition,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks GMSS: Graph-Based Multi-Task Se lf-Supervised Learning for EEG Emotion Recognition,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-16T05:25:32.703540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:25:32.703540Z digest=sha256:f82f69c5c8629793ebad1d43e42a94ad6d45a95914cdfb107c1ba8b674dede6e

Observation 77deee90-5ece-46c7-8645-4df12e077998 · outbound

This paper cites MSFR-GCN: A Multi-Scale Feature Reconstruction Graph Convolutional Network for EEG Emotion and Cognition Recognition,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks MSFR-GCN: A Multi-Scale Feature Reconstruction Graph Convolutional Network for EEG Emotion and Cognition Recognition,

Reference 39

Resolution
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no resolver link, observed 2026-08-16T05:25:32.708249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:25:32.708249Z digest=sha256:a6c5c821897fe6ca6ccfd2b263b740c40382fbb7dc7302a5b9e100600abfc9b4

Observation 67f8d93b-cac5-48ed-b22a-d6a942eaf4bf · outbound

This paper cites Emotio n Recognition Using Hierarchical Spatiotemporal Electroencephalogram In formation from Local to Global Brain Regions,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Emotio n Recognition Using Hierarchical Spatiotemporal Electroencephalogram In formation from Local to Global Brain Regions,

Reference 40

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-16T05:25:32.712806Z digest=sha256:1e797ac0ebc92f20db32a4ff2065d04e1d1519ccdd661d68cb62f93591e6331b

Observation 26211c75-9cdc-4c88-9eac-ee8baff2c3a5 · outbound

This paper cites E EG emotion recognition using EEG-SWTNS neural network through EEG spectral image,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks E EG emotion recognition using EEG-SWTNS neural network through EEG spectral image,

Reference 41

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metadata mismatch
raw_fallback, observed 2026-08-16T05:25:33.289703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-16T05:25:32.717554Z digest=sha256:58182350d736f47865e849fd6a7140caa92b7af071afdbbdcc59f879159b4fa4

Observation d87d43aa-bbbe-479d-a4a0-0a9ca8d83fe0 · outbound

This paper cites Graph Convolutional Network Wi th Connectivity Uncertainty for EEG-Based Emotion Recognition,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks Graph Convolutional Network Wi th Connectivity Uncertainty for EEG-Based Emotion Recognition,

Reference 42

Resolution
metadata mismatch
raw_fallback, observed 2026-08-16T05:25:33.210719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-16T05:25:32.722463Z digest=sha256:55cf1d5cb6787c36896ef8b869d34f13eeaa1229a209fc532ce087f95702a04b

Observation 1950e088-29c1-4dc9-8eac-9864e141f821 · outbound

This paper cites EEG-based emotion recognition using a temporal-difference minimizing neural network,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks EEG-based emotion recognition using a temporal-difference minimizing neural network,

Reference 43

Resolution
verified exact
doi, observed 2026-08-16T05:25:32.772851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-16T05:25:32.727555Z digest=sha256:91509fc2e7664f44a6eaffec1e33de6b1a64da59aeac01d9233de295b69bb2ed

Observation db3a03f0-5acf-419f-8bf8-a60cfa7abe54 · outbound

This paper cites An Efficient Graph Learning Sys tem for Emotion Recognition Inspired by the Cognitive Prior Graph o f EEG Brain Network,.

DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks An Efficient Graph Learning Sys tem for Emotion Recognition Inspired by the Cognitive Prior Graph o f EEG Brain Network,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-16T05:25:32.732323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:25:32.732323Z digest=sha256:af700decebc7f6d88af4ba751793a2d7af8500b41e8094881f4f587d9bd37e29

Pith citing papers

No inbound Pith citation observations are available.