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fusion-research's Projects

ma_et_al_2017_code icon ma_et_al_2017_code

Attempt at replicating the code for proposed method of Ma et al. 2017 "Exploiting Deep Neural Networks and Head Movements for Robust Binaural Localization of Multiple Sources in Reverberant Environments"

mc_stgcn icon mc_stgcn

A multi-community spatio-temporal graph convolutional network (MC_STGCN) for passenger demand forecasting at multi-region level

mdp_tracking icon mdp_tracking

Learning to Track: Online Multi-Object Tracking by Decision Making

merlion icon merlion

Merlion: A Machine Learning Framework for Time Series Intelligence

metahin icon metahin

Source code for KDD 2020 paper "Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation"

misaga icon misaga

Algorithm MISAGA published in IEEE TCYB (2017)-Graph clustering, community detection, attributed graph, graph analytics

ml-youtube-courses icon ml-youtube-courses

A repository to index and organize the latest machine learning courses found on YouTube.

mlops-specialization-notes icon mlops-specialization-notes

Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng

mnc icon mnc

Instance-aware Semantic Segmentation via Multi-task Network Cascades

movingpandas icon movingpandas

Implementation of Trajectory classes and functions built on top of GeoPandas

mr-efs icon mr-efs

This project includes the implementation of evolutionary feature selection models based on MapReduce.

mrmml-v1.0 icon mrmml-v1.0

A Matlab implementation of our previously published work in IEEE Trans. Big Data (TBD)

mrpr icon mrpr

This repository includes the MapReduce implementation proposed for Prototype Reduction in [1].

msda icon msda

multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

mt3 icon mt3

Code for the paper "Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning" (https://arxiv.org/abs/2104.00734).

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