Math+ML+X Lab (Math-ML-X)

Math+ML+X Lab

Math-ML-X

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Math+ML+X Lab's repositories

cUNet

Website of Continuous U-Net: https://math-ml-x.github.io/cUNet/

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2019_mri_reconstruction

Implementation of MRIR-DLMC algorithm

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DAL-HERS

HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation

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Diff4Med

Website for 'From Theory to Treatment: Advancing Diffusion Models for Medical Diagnosis': https://math-ml-x.github.io/Diff4Med/

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DiffMIC

DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification

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GraphMIA24

This is the official website for MICCAI'24 Tutorial on Graph Learning in Medical Image Analysis.

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LaplaceNet

A PyTorch Implementation of LaplaceNet:A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification

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NorMatch

PyTorch implementation of NorMatch paper (TMLR)

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ORACLE

Website for 'AI Based Traffic Analysis from Video Data for Assessing Pollution Levels, Road Safety and Population Health in Major Cities': https://math-ml-x.github.io/ORACLE/

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scotch-and-soda

[CVPR'23] Code for "SCOTCH and SODA: A Transformer Video Shadow Detection Framework".

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simultaneous_semantic_and_instance_segmentation

[MIUA'22 & CoNiC'22] Code for "Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting".

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Superpixel-Contracted-Graph-Based-Learning-for-Hyperspectral-Image-Classification

Code for the Paper "Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification"

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TFPnP

Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems (ICML 2020 Award Paper & JMLR 2022)

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ThreeStageSelftraining_SemanticSegmentation

This repository is about our work "A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation"

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TrafficCAM

Website of TrafficCAM: https://math-ml-x.github.io/TrafficCAM/

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TRIDENT

Website of TRIDENT: https://math-ml-x.github.io/TRIDENT/

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unsupervised-medical-image-segmentation

Code for "Contrastive Registration for Unsupervised Medical Image Segmentation".

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GrapHMedIA

Website for MICCAI 2023 Tutorial: https://math-ml-x.github.io/GrapHMedIA/

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