State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
- computer-vision
- deep-learning
- drug-discovery
- forecasting
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State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
A scikit-learn compatible neural network library that wraps PyTorch
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.
Brain Computer Interface to drive car using brain.