Efficiently computes derivatives of NumPy code.
- autograd
- automatic-differentiation
- numpy
- python
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Efficiently computes derivatives of NumPy code.
A PyTorch Library for Accelerating 3D Deep Learning Research
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
Message Passing Neural Networks for Molecule Property Prediction
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
Brian is a free, open source simulator for spiking neural networks.
Python package for graph neural networks in chemistry and biology
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry
A Euclidean diffusion model for structure-based drug design.
Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.
Sequential regulatory activity predictions with deep convolutional neural networks.
Neural networks toolbox focused on medical image analysis
GraphDTA: Predicting drug-target binding affinity with graph neural networks
Source code for "DeepDTA: deep drug-target binding affinity prediction"
RNA-seq prediction with deep convolutional neural networks.
A tool for cell instance aware segmentation in densely packed 3D volumetric images
Axon/Myelin segmentation using Deep Learning
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
Cryptographic Dataset Generation & Modelling Framework