Machine Intelligence Laboratory

CE_SCST

Pytorch implementation of "Enhancing Contextual Encoding with Stage-confusion and Stage-transition Estimation for EEG-based Sleep Staging"

DeepLearningTutorial

Deep Learning tutorial

EAG-RS

EAG-RS: A Novel Explainability-guided ROI Selection Framework for ASD diagnosis via Inter-regional Relation Learning - PyTorch Implementation (IEEE-TMI 2023)

LEAR

Tensorflow implementation of "Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model"

LiCoL

MGICNN

Implementation of "Multi-scale Gradual Itegration Convolutional Neural Network for False Positive Reduction in Pulmonary Nodule Detection"

PL-FC

rDNN

Implementation of "Toward an Interpretable Alzheimer's Disease Diagnostic Model with Regional Abnormality Representation via Deep Learning"

TransSleep

A source code for deep learning-based autonomous sleep staging.

V-RIN

Implementation of "Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series"

ku-milab/LEAR

Tensorflow implementation of "Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model"

ku-milab/PL-FC

ku-milab/EAG-RS

EAG-RS: A Novel Explainability-guided ROI Selection Framework for ASD diagnosis via Inter-regional Relation Learning - PyTorch Implementation (IEEE-TMI 2023)

ku-milab/LiCoL

ku-milab/CE_SCST

Pytorch implementation of "Enhancing Contextual Encoding with Stage-confusion and Stage-transition Estimation for EEG-based Sleep Staging"

ku-milab/Deep-Efficient-Continuous-Manifold-Learning

ku-milab/GMBA

Pytorch implementation of "Age-Aware Guidance via Masking-Based Attention in Face Aging" [CIKM 2023]

ku-milab/PG-BrainBagNet

ku-milab/TransSleep

A source code for deep learning-based autonomous sleep staging.

ku-milab/XADLiME

We propose a novel deep-learning approach through eXplainable AD Likelihood Map Estimation (XADLiME) for AD progression modeling over 3D sMRIs using clinically-guided prototype learning

ku-milab/Deep-Geometric-AD

ku-milab/ENGINE

A deep learning framework for imaging genetics

ku-milab/FIESTA

ku-milab/FMM

Frequency Mixup Manipulation based Unsupervised Domain Adaptation for Brain Disease Identification

ku-milab/GCN_Informative_Regional_Relation_Representation

ku-milab/learnable-counter-condition-FC

What if patients were recovered? A learnable counter-condition analysis framework for functional connectivity-based ASD diagnosis

ku-milab/MoANA

Pytorch implementation of "MoANA: Module of Axis-based Nexus Attention for Weakly Supervised Object Localization and Semantic Segmentation"

ku-milab/RSTNN

Implementation of "Deep recurrent spatio-temporal neural network for motor imagery based BCI"

ku-milab/UHF-guided_segmentation

PyTorch implementation of "Transferring Ultra-high Field Representations for Intensity-Guided Brain Segmentation of Low Field MRI"

ku-milab/ADT2R

Pytorch implementation of "Adaptive Decision Transformer for Dynamic Treatment Regimes in Sepsis"

ku-milab/BrainWaveNet

Official implementation of "BrainWaveNet: Wavelet-based Transformer for Autism Spectrum Disorder Diagnosis" (MICCAI 2024)

ku-milab/Counterfactual-Inference-in-Diffusion-Models

ku-milab/DIPNet

Repo for Dual Information Pathways Network (DIPNet) which developed to represent unarticulated speech EEG

ku-milab/ESTA

ku-milab/IdenBAT

ku-milab/Meta-Modulation-GenM

ku-milab/MSNN

Implementation of "Multi-Scale Neural Network for EEG Representation Learning in BCI"

ku-milab/RL_BCI

Implementation of "A Novel RL-assisted Deep Learninng Framework for Task-informative Signals Selection and Classification for Spontaneous BCIs"

ku-milab/SFCNR

ku-milab/SGDAL