Popular GitHub Repositories for Electre Iii

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

BioWordVec & BioSentVec: pre-trained embeddings for biomedical words and sentences

BlueBERT, pre-trained on PubMed abstracts and clinical notes (MIMIC-III).

i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (channel attention) and *temporal dimension*. iii. Common spatial pattern (CSP), an efficient feature enhancement method, realized with Python.

[ECCV 2024] Improving 2D Feature Representations by 3D-Aware Fine-Tuning

Curiosity-driven Exploration by Self-supervised Prediction for Street Fighter III Third Strike

IJCAI2021: Code for SafeDrug, MIMIC data processing, Medical code mapping

Code for the paper: Multi-Label Clinical Time-Series Generation via Conditional GAN (IEEE TKDE)

Learning from Discharge Summaries to extract mentioned diagnoses using Hierarchical Attention Model

Rare disease identification from free-text clinical notes with ontologies and weak supervision

Time-Sensitive Deep Learning for ICU Outcome Prediction Without Variable Selection or Cleaning.

Master's project

Jax/Flax implementation of DeiT and DeiT-III (ViT)

Early prediction of sepsis with gradient boosting (XGBoost) and deep learning (LSTM and GRU) using MIMIC-III data.

MEME: Generating RNN Model Explanations via Model Extraction

Deep neural network trained to drive Need For Speed III: Hot Pursuit

A new approach to extract clinical summaries from discharge notes

Repository for the Paper: ?On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series“

ASHRAE - Great Energy Predictor III: How much energy will a building consume?

An machine learning based AI for the Halite III competition.