This is a simple package wrapping py3dmol for a single command visualization of a RDKit molecule and its conformations (embed as Conformer objects in the Molecule)
pip install molconfviewer
from molconfviewer import MolConfViewer
mol_conf_viewer = MolConfViewer()
mol_conf_viewer.view(mol=mol) # where mol is a rdkit mol
See the MolConfViewer object code to customize the visualization. For more possibilities, please check py3dmol and 3dmol.js.
Correlation Explanation Methods Official implementation of linear correlation explanation (linear CorEx) and temporal correlation explanation (T-CorEx
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A collection of research papers and software related to explainability in graph machine learning.
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.
tensorboardX Write TensorBoard events with simple function call. The current release (v2.1) is tested on anaconda3, with PyTorch 1.5.1 / torchvision 0
🤪 TensorFlowTTS provides real-time state-of-the-art speech synthesis architectures such as Tacotron-2, Melgan, Multiband-Melgan, FastSpeech, FastSpeech2 based-on TensorFlow 2. With Tensorflow 2, we c
⬛ PyCEbox Python Individual Conditional Expectation Plot Toolbox A Python implementation of individual conditional expecation plots inspired by R's IC
TreeInterpreter Package for interpreting scikit-learn's decision tree and random forest predictions. Allows decomposing each prediction into bias and
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