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Name: Machine Intelligence Laboratory
Type: Organization
Bio: Machine Intelligence Laboratory @ Korea University
Location: 510, Science Library, Korea University 145 Anam-Ro, Seongbuk-Gu, Seoul 02841, Korea
Name: Machine Intelligence Laboratory
Type: Organization
Bio: Machine Intelligence Laboratory @ Korea University
Location: 510, Science Library, Korea University 145 Anam-Ro, Seongbuk-Gu, Seoul 02841, Korea
Pytorch implementation of "Adaptive Decision Transformer for Dynamic Treatment Regimes in Sepsis"
Tensorflow implementation of "Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision"
Pytorch implementation of "Enhancing Contextual Encoding with Stage-confusion and Stage-transition Estimation for EEG-based Sleep Staging"
Implementation of "Domain Adaptation with Source Selection for Motor-Imagery Based BCI"
Implementation of "Deep Recurrent Model for Individualized Prediction of Alzheimer’s Disease Progression"
Deep Learning tutorial
Repo for Dual Information Pathways Network (DIPNet) which developed to represent unarticulated speech EEG
EAG-RS: A Novel Explainability-guided ROI Selection Framework for ASD diagnosis via Inter-regional Relation Learning - PyTorch Implementation (IEEE-TMI 2023)
Implementation of "Identifying Resting-State Effective Connectivity Abnormalities in Drug-Naïve Major Depressive Disorder Diagnosis via Graph Convolutional Networks"
A deep learning framework for imaging genetics
Tensorflow implementation of "Plug-in Factorization for Latent Representation Disentanglement"
Frequency Mixup Manipulation based Unsupervised Domain Adaptation for Brain Disease Identification
Pytorch implementation of "Age-Aware Guidance via Masking-Based Attention in Face Aging" [CIKM 2023]
Tensorflow implementation of "Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model"
Implementation of "Multi-scale Gradual Itegration Convolutional Neural Network for False Positive Reduction in Pulmonary Nodule Detection"
Pytorch implementation of "Multi-view Integration Learning for Irregularly-sampled Clinical Time Series" (Under review, JBHI)
Pytorch implementation of "MoANA: Module of Axis-based Nexus Attention for Weakly Supervised Object Localization and Semantic Segmentation"
Implementation of "Multi-Scale Neural Network for EEG Representation Learning in BCI"
Implementation of "Deep Learning-based Brain Tumor Segmentation from Multi-modal MRI"
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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An Open Source Machine Learning Framework for Everyone
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.