Starred repositories
171
results
for source starred repositories
Clear filter
A repository consisting of paper/architecture replications of classic/SOTA AI/ML papers in pytorch
Collect optimizer related papers, data, repositories
📈Implementing the ADAM optimizer from the ground up with PyTorch and comparing its performance on six 3-D objective functions (each progressively more difficult to optimize) against SGD, AdaGrad, a…
Application of Graph Neural Networks in accurate prediction of polypharmacy side effects.
Repository for implementation of generative models with Tensorflow 1.x
Math Course Materials of SUSTech
In this repository, we implement Targeted Meta-Learning (or Targeted Data-driven Regularization) architecture for training machine learning models with biased data.
Self-Supervised Bayesian Representation Learning of Acoustic Emissions from Laser Powder Bed Fusion Process for In-situ Monitoring
Network analysis and visualization of drug-drug interactions with NetworkX and Pyvis
Useful resources on data quality for machine learning and artificial intelligence.
22
Updated Apr 14, 2025
Attention-based Hybrid CNN-LSTM and Spectral Data Augmentation for COVID-19 Diagnosis from Cough Sound
Bayesian optimisation & Reinforcement Learning library developed by Huawei Noah's Ark Lab
NUS CS5284 Graph Machine Learning course, Xavier Bresson, 2024
Graph Machine Learning course, Xavier Bresson, 2023
MATH3431 - Machine Learning and Neural Networks III (Epiphany 2024)
🧬 Network analysis between Protein-Protein interaction
From Theory to Practice: Statistical and Machine Learning (StatML)
bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.
Repository for Distributed representations of graphs for drug pair scoring
Prediction molecular structure from NMR spectra
Advanced Data Structures Implementation
Repository for course works and materials, KMITL Msc in Data Science and Data Analytics.
A python package for chemical space visualization.
A deep learning framework for predicting chemical synthesis
Implementation of Ensemble Principal Component Analysis (EPCA).
The code of a graph neural network (GNN) for molecules, which is based on learning representations of r-radius subgraphs (i.e., fingerprints) in molecules.