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EEG

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/maxxxzdn/eegvae

공식 코드

Learning Generative Factors of EEG Data with Variational auto-encoders

https://github.com/mcd4874/neurips_competition

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2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets

https://github.com/mdfahimanjum/lipcot

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LiPCoT: Linear Predictive Coding based Tokenizer for Self-supervised Learning of Time Series Data via Language Models

https://github.com/medmaxlab/eegpartition

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The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: a preliminary study

https://github.com/medmaxlab/eegprepro

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The more, the better? Evaluating the role of EEG preprocessing for deep learning applications

https://github.com/medmaxlab/selfeeg

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SelfEEG: A Python library for Self-Supervised Learning in Electroencephalography

https://github.com/meiyor/SincNet-for-Autism-EEG-based-Emotion-Recognition

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Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity

https://github.com/meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals

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Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism

https://github.com/mengchillee/gen2out

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gen2Out: Detecting and Ranking Generalized Anomalies

https://github.com/metaverse-crowdsource/eeg-tes-chaos-neural-net

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Artificial Intelligence for EEG Prediction: Applied Chaos Theory

https://github.com/miaozhengqing/lmda-code

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LMDA-Net:A lightweight multi-dimensional attention network for general EEG-based brain-computer interface paradigms and interpretability

https://github.com/miaozhengqing/tsff

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Time-space-frequency feature Fusion for 3-channel motor imagery classification

https://github.com/miaozhengqing/weightfreezing

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Weight Freezing: A Regularization Approach for Fully Connected Layers with an Application in EEG Classification

https://github.com/micholeodon/ToFFi_Toolbox

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ToFFi -- Toolbox for Frequency-based Fingerprinting of Brain Signals

https://github.com/mike-boop/match-mismatch-decoders-ojsp-2023

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Decoding Envelope and Frequency-Following EEG Responses to Continuous Speech Using Deep Neural Networks

https://github.com/mikewangwzhl/eeg-to-text

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Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification

https://github.com/miltoncandela/neurohumanities-lab

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Real-time EEG-based Emotion Recognition Model using Principal Component Analysis and Tree-based Models for Neurohumanities

https://github.com/mims-harvard/tfc-pretraining

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Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency

https://github.com/mininglamp-mllm/hmllm

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Hypergraph Multi-modal Large Language Model: Exploiting EEG and Eye-tracking Modalities to Evaluate Heterogeneous Responses for Video Understanding

https://github.com/miracle-2001/gnn4eeg

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GNN4EEG: A Benchmark and Toolkit for Electroencephalography Classification with Graph Neural Network

https://github.com/mirfaridmusavian/deepcsp

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Graph Convolutional Neural Networks for analysis of EEG signals, BCI application

https://github.com/mistlab/portiloop

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The Portiloop: a deep learning-based open science tool for closed-loop brain stimulation

https://github.com/mmurrad/eeg-to-text

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EEG-to-Text Translation: A Model for Deciphering Human Brain Activity

https://github.com/mobile-sensing-and-ubicomp-laboratory/normwear

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Toward Foundation Model for Multivariate Wearable Sensing of Physiological Signals

https://github.com/moeinrazavi/OpenSync_Unity

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OpenSync: An opensource platform for synchronizing multiple measures in neuroscience experiments

https://github.com/mrsfgl/supervised-tensor-fusion

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Coupled Support Tensor Machine Classification for Multimodal Neuroimaging Data

https://github.com/mtanveer1/RoBoSS

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RoBoSS: A Robust, Bounded, Sparse, and Smooth Loss Function for Supervised Learning

https://github.com/muyang99/mptsnet

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MPTSNet: Integrating Multiscale Periodic Local Patterns and Global Dependencies for Multivariate Time Series Classification

https://github.com/muzixiang/si-cleer

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A Supervised Information Enhanced Multi-Granularity Contrastive Learning Framework for EEG Based Emotion Recognition

https://github.com/nanbhas/trustlapse

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TRUST-LAPSE: An Explainable and Actionable Mistrust Scoring Framework for Model Monitoring

https://github.com/navidfoumani/eeg2rep

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EEG2Rep: Enhancing Self-supervised EEG Representation Through Informative Masked Inputs

https://github.com/navsnav/RBD-Sleep-Detection

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Detection of REM Sleep Behaviour Disorder by Automated Polysomnography Analysis

https://github.com/nbahador/-fine_tuned_gpt2_model_on_epilepsy_related_pubmed_abstracts

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Localized Definitions and Distributed Reasoning: A Proof-of-Concept Mechanistic Interpretability Study via Activation Patching

https://github.com/ncclabsustech/EEGdenoiseNet

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EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising

https://github.com/ncclabsustech/Single-Channel-EEG-Denoise

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EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising

https://github.com/ncclabsustech/deepseparator

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Embedding Decomposition for Artifacts Removal in EEG Signals

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.