PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition | Paper Citation Record

Observation db0e798b-38c3-451a-926f-75a683646572 · outbound

This paper cites Matt: A manifold attention network for eeg decoding,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Matt: A manifold attention network for eeg decoding,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.187139Z

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Observation ac707779-4d58-4ca4-8fbc-333fb064f0b5 · outbound

This paper cites Spd domain- specific batch normalization to crack interpretable unsupervised domain adaptation in eeg,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Spd domain- specific batch normalization to crack interpretable unsupervised domain adaptation in eeg,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.238041Z

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No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 8f5eacec-4372-4f35-b6f6-3399cc5e8c6b · outbound

This paper cites Frontal eeg asymmetry as a moderator and mediator of emotion,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Frontal eeg asymmetry as a moderator and mediator of emotion,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.228456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 0ef58d6e-4de9-415b-b3a4-814aca4b9116 · outbound

This paper cites Astdf-net: attention- based spatial-temporal dual-stream fusion network for eeg-based emo- tion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Astdf-net: attention- based spatial-temporal dual-stream fusion network for eeg-based emo- tion recognition,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.230489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 3681fedc-6851-475d-a78c-129a24333e17 · outbound

This paper cites Multi- view domain-adaptive representation learning for eeg-based emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Multi- view domain-adaptive representation learning for eeg-based emotion recognition,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.232414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 7e30f66d-0402-4bf8-a536-e6febe0617a0 · outbound

This paper cites Seeg emotion recognition based on transformer network with channel selection and explainability,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Seeg emotion recognition based on transformer network with channel selection and explainability,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.236173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 72e99905-1f03-467b-901d-bcaf53ffd837 · outbound

This paper cites mimamba: Eeg-based emotion recognition with multi-scale inverted mamba models,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition mimamba: Eeg-based emotion recognition with multi-scale inverted mamba models,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.255236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 6f1ef5e8-2e7d-478c-b8b7-01875014707d · outbound

This paper cites Eeg- based emotion recognition via channel-wise attention and self attention,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Eeg- based emotion recognition via channel-wise attention and self attention,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.218405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation a3015070-a05e-4f65-976c-3f1e7206d91f · outbound

This paper cites Eeg emotion recog- nition using improved graph neural network with channel selection,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Eeg emotion recog- nition using improved graph neural network with channel selection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.189059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 9951d8a8-1022-429b-814c-29b1627c80d9 · outbound

This paper cites Automatically extracting and utilizing eeg channel importance based on graph convolutional network for emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Automatically extracting and utilizing eeg channel importance based on graph convolutional network for emotion recognition,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.216522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 49626f70-bc63-4c27-95cf-b46b8a9ebe85 · outbound

This paper cites Eegmatch: Learning with incomplete labels for semisupervised eeg-based cross-subject emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Eegmatch: Learning with incomplete labels for semisupervised eeg-based cross-subject emotion recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.220249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation ed53a0da-d647-4707-9d3e-4bc63a354045 · outbound

This paper cites Multi-modal cross-subject emotion feature alignment and recognition with eeg and eye movements,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Multi-modal cross-subject emotion feature alignment and recognition with eeg and eye movements,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.234251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation c3e6581c-b831-46e6-9d75-6e3ab7587e54 · outbound

This paper cites Gusa: Graph-based unsuper- vised subdomain adaptation for cross-subject eeg emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Gusa: Graph-based unsuper- vised subdomain adaptation for cross-subject eeg emotion recognition,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.208454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation f37d12eb-248b-47cc-86d6-1b5959351225 · outbound

This paper cites Domain adversarial neural network with reliable pseudo-labels iteration for cross-subject eeg emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Domain adversarial neural network with reliable pseudo-labels iteration for cross-subject eeg emotion recognition,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.199161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation b4d4b452-8a2e-467f-975a-685fb4f9827c · outbound

This paper cites Semi-supervised dual-stream self-attentive adversarial graph contrastive learning for cross-subject eeg-based emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Semi-supervised dual-stream self-attentive adversarial graph contrastive learning for cross-subject eeg-based emotion recognition,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.192995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 5dce7928-e42d-4732-a29f-c4d10667e74e · outbound

This paper cites Unsupervised time-aware sampling network with deep reinforcement learning for eeg-based emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Unsupervised time-aware sampling network with deep reinforcement learning for eeg-based emotion recognition,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.226476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 67307efe-6881-4ff1-9f9d-7172c6c7dc44 · outbound

This paper cites Brainuicl: An unsupervised individual continual learning framework for eeg applications.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Brainuicl: An unsupervised individual continual learning framework for eeg applications

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.249423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation d2b0828e-6abf-4bec-b3be-c753890b8643 · outbound

This paper cites Learning Factored Representations in a Deep Mixture of Experts.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Learning Factored Representations in a Deep Mixture of Experts

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-07-02T16:47:08.975311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation c40438ef-b832-429c-9379-48e43e987f21 · outbound

This paper cites AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:47:08.972875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 462a3ecf-6ddd-4503-a753-18f7040ca46a · outbound

This paper cites Emt: A novel transformer for generalized cross-subject eeg emotion 11 recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Emt: A novel transformer for generalized cross-subject eeg emotion 11 recognition,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.204703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation fc818546-672e-4820-8d31-b59560da960e · outbound

This paper cites Eeg emotion recognition using attention-based convolutional transformer neural network,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Eeg emotion recognition using attention-based convolutional transformer neural network,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.206531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 6af2988b-e31e-4ed5-82fe-3dedc4fb930a · outbound

This paper cites Convolutional gated recurrent unit-driven mul- tidimensional dynamic graph neural network for subject-independent emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Convolutional gated recurrent unit-driven mul- tidimensional dynamic graph neural network for subject-independent emotion recognition,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.182661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation a4c73ec8-ef50-4cc3-8fb7-c0ac583c45a8 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.180619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 6a6160d6-7f24-4044-8b74-c6498dd5e12e · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-07-02T16:47:08.980435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 8a3cfe87-f342-4e15-96e4-5962bcedb7f1 · outbound

This paper cites Scaling vision with sparse mixture of experts.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Scaling vision with sparse mixture of experts

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.197159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation ca2b48c1-1ba4-455a-a4a6-a6e7cd2f947f · outbound

This paper cites Variational mixture-of-experts autoen- coders for multi-modal deep generative models,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Variational mixture-of-experts autoen- coders for multi-modal deep generative models,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.184605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 0a5443b7-ad4e-437f-8e59-f41d45210d59 · outbound

This paper cites Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:47:08.989098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 4075a79a-87e3-4806-84fd-67140beec052 · outbound

This paper cites Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:47:08.998406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation df29d581-5d69-42b7-b40a-811d3f4cb0d4 · outbound

This paper cites Shedding light on time series classification using interpretability gated networks,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Shedding light on time series classification using interpretability gated networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.176582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation d0076976-7e6f-4b31-b63f-2b090f35ab81 · outbound

This paper cites Learning Soft Sparse Shapes for Efficient Time-Series Classification.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Learning Soft Sparse Shapes for Efficient Time-Series Classification

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:47:08.970152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 3e63a59d-8f81-45fe-8b98-689d0bc38377 · outbound

This paper cites Mixmatch: A holistic approach to semi-supervised learning,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Mixmatch: A holistic approach to semi-supervised learning,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.202859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 24aa819a-f6d1-449c-8e08-cb24c889dd3c · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition mixup: Beyond Empirical Risk Minimization

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-07-02T16:47:08.978035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 3a80ae92-0e6c-4b9e-ae3d-13425e82f09b · outbound

This paper cites Fixmatch: Simplifying semi- supervised learning with consistency and confidence.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Fixmatch: Simplifying semi- supervised learning with consistency and confidence

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.214185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation bf1277f7-98d8-45ea-899c-c2c53fdbda96 · outbound

This paper cites Flexmatch: Boosting semi-supervised learning with curriculum pseudo labeling,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Flexmatch: Boosting semi-supervised learning with curriculum pseudo labeling,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.201022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation f2e4fb03-26ce-4c3b-903f-426572652d6c · outbound

This paper cites FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:47:08.983508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation a108f77c-8401-4255-bfe9-631d3467e0eb · outbound

This paper cites SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:47:08.995273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation bbb03c06-1dae-45cf-bd64-849c180cbf05 · outbound

This paper cites AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:47:08.972645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 87398b7d-df0e-481b-8d63-62e97ae827e0 · outbound

This paper cites Boosting semi-supervised learning by exploiting all unlabeled data,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Boosting semi-supervised learning by exploiting all unlabeled data,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.253401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation d17980de-faab-4305-a1ab-8131b830b04c · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-07-02T16:47:08.967211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 0e8426ba-ff91-4b8e-a83d-eb9dd20f3d37 · outbound

This paper cites Fedformer: Frequency enhanced decomposed transformer for long-term series fore- casting.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Fedformer: Frequency enhanced decomposed transformer for long-term series fore- casting

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.251562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation f33c10e1-3f5a-486d-b71c-41b5755418b6 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-07-02T16:47:08.986449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation cdbf2ada-40f4-41e9-9710-a9df6133d83d · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-07-02T16:47:08.992289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 6c698641-1211-42ef-a705-8785340c50ac · outbound

This paper cites Deap: A database for emotion analysis; using physiological signals.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Deap: A database for emotion analysis; using physiological signals

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.210412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 3df7793b-054d-43b7-8c94-a83884017fdd · outbound

This paper cites Dreamer: A database for emotion recognition through eeg and ecg signals from wireless low-cost off- the-shelf devices,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Dreamer: A database for emotion recognition through eeg and ecg signals from wireless low-cost off- the-shelf devices,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.178505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation e916c6de-7550-4ee1-b232-95fb0bbc72ef · outbound

This paper cites Investigating critical frequency bands and channels for eeg-based emotion recognition with deep neural networks.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Investigating critical frequency bands and channels for eeg-based emotion recognition with deep neural networks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.224242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 18d08cc9-c2bd-47c2-bfff-630f6f1913b5 · outbound

This paper cites Are transformers effective for time series forecasting?.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Are transformers effective for time series forecasting?

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.222124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 17e6ebbf-3fb2-4bec-a362-71c220ce00f5 · outbound

This paper cites Non-stationary transformers: Exploring the stationarity in time series forecasting.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Non-stationary transformers: Exploring the stationarity in time series forecasting

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.212335Z

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Observation b93850b0-1a04-4b02-bab9-79de597d1273 · outbound

This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.191018Z

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Observation 50173335-9573-45b9-a5f2-950a24867c9c · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-07-02T16:47:08.977714Z

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Observation 746df819-ea4d-47ca-a51b-da1a6eba67bd · outbound

This paper cites A novel transformer autoencoder for multi-modal emotion recognition with incomplete data,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition A novel transformer autoencoder for multi-modal emotion recognition with incomplete data,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.243688Z

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No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation ac0b7dc5-19c6-4f5b-8672-00cbc1756a51 · outbound

This paper cites Dynamic stream selection network for subject-independent eeg-based emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Dynamic stream selection network for subject-independent eeg-based emotion recognition,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.195049Z

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Observation 0995a49a-44ee-4f8b-8735-479437bc5418 · outbound

This paper cites Cascaded Self-supervised Learning for Subject-independent EEG-based Emotion Recognition.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Cascaded Self-supervised Learning for Subject-independent EEG-based Emotion Recognition

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:47:08.964464Z

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No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 0b2da362-9882-4bc6-89ba-c47c33742f67 · outbound

This paper cites Gddn: Graph domain disen- tanglement network for generalizable eeg emotion recognition,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Gddn: Graph domain disen- tanglement network for generalizable eeg emotion recognition,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.245565Z

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No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 9cc68fa3-013a-4c90-9522-6b601e6a7369 · outbound

This paper cites Subject independent emotion recognition using eeg signals employing attention driven neural net- works,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Subject independent emotion recognition using eeg signals employing attention driven neural net- works,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.247461Z

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No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 069e53f1-1dcc-4c61-826c-46e11aa814b6 · outbound

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

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Alpha-band oscillations, attention, and controlled access to stored information

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.240053Z

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No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.

Observation 47ad56fd-bef4-4046-bb26-3f0726a257c1 · outbound

This paper cites How brains beware: neural mechanisms of emotional attention,.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition How brains beware: neural mechanisms of emotional attention,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T23:01:33.241891Z

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