yjhan99

yjhan99's Stars

• natashamjaques/MultimodalAutoencoder

  Code supporting the paper "Multimodal Autoencoder: A Deep Learning Approach to Filling In Missing Sensor Data and Enabling Better Mood Prediction"

  Language:Python7230

• mitmedialab/PersonalizedMultitaskLearning

  Code for performing 3 multitask machine learning methods: deep neural networks, Multitask Multi-kernel Learning (MTMKL), and a hierarchical Bayesian model (HBLR).

  Language:Python12560

• Emognition/dl-4-tsc

  Deep Learning for Time Series Classification

  Language:Python134

• Kaist-ICLab/K-EmoCon_SupplementaryCodes

  Supplementary codes for the K-EmoCon dataset

  Language:Python2311

• Kaist-ICLab/K-EmoPhone_SupplementaryCodes

  Data analysis codes for the K-EmoPhone dataset

  Language:Jupyter Notebook52

• usc-sail/tiles-dataset-release

  Code accompanying the TILES dataset paper and data release. Data at https://tiles-data.isi.edu.

  Language:R6

• Kaist-ICLab/old-homepage

  Language:TypeScript41

• Steppschuh/Sensor-Data-Logger

  Android Wear sensor data plotter

  Language:Java20273

• android/wear-os-samples

  Multiple samples showing best practices in app and watch face development on Wear OS.

  Language:Kotlin1.1k569

• haifengl/smile

  Statistical Machine Intelligence & Learning Engine

  Language:Java6k1.1k

• thomasnield/kotlin-machine-learning-demos

  Demonstration of several machine learning algorithms in Kotlin

  Language:Kotlin587

• adap/flower

  Flower: A Friendly Federated Learning Framework

  Language:Python4.9k843

• SunitRoy2703/Tensorflow-lite-kotlin-samples

  📌This repo contains the kotlin implementation of TensorflowLite Example Android Apps🚀

  Language:Kotlin449

• nnarziev/MINDSCOPE_Client

  StressSensor Android application using gRPS

  Language:Java21

• coitloz88/Android-Stress-Intervention

  Stress feedback derived from HRV provided in real time

  Language:Kotlin1

• davedoesdemos/ConnectIQ-Watch-IoT

  This is a Connect IQ app for Garmin devices. It will send data in realtime to Azure via the Connect Mobile app.

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