Pinned Repositories
Advanced-Deep-Learning-with-Keras
Advanced Deep Learning with Keras, published by Packt
aiida-environ
AlphaCrystal
AlphaCrytal: Contact map based deep learning algorithm for crystal structure prediction
ase
Atomic Simulation Environment - mirror of https://gitlab.com/ase/ase
ase-espresso
ase interface for Quantum Espresso
basic_simulation_training
A document for the Living Journal of Computational Molecular Science (LiveCoMS) which describes basic training for molecular simulations (oriented towards molecular dynamics (MD)), providing some training itself and linking out to other helpful information elsewhere. The intent is that this provide information on the prerequisites which will be required for understanding/following many of the other "best practices" documents being prepared.
cgcnn
Crystal graph convolutional neural networks for predicting material properties.
scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
pradipchm's Repositories
pradipchm/scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
pradipchm/aiida-environ
pradipchm/AlphaCrystal
AlphaCrytal: Contact map based deep learning algorithm for crystal structure prediction
pradipchm/ase
Atomic Simulation Environment - mirror of https://gitlab.com/ase/ase
pradipchm/cgcnn
Crystal graph convolutional neural networks for predicting material properties.
pradipchm/CIGIN
AAAI 2020: Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-like Molecules
pradipchm/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
pradipchm/dl-chem-101
Example implementations of common machine learning projects in chemistry.
pradipchm/dmol-book
Deep learning for molecules and materials book
pradipchm/LaPreprint
📝 A nicely formatted LaTeX preprint template
pradipchm/geometric-gnns
List of Geometric GNNs for 3D atomic systems
pradipchm/handson-ml3
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
pradipchm/ipython-wiki
manual mirror of ipython-wiki for discussion.
pradipchm/MatDeepLearn
MatDeepLearn, package for graph neural networks in materials chemistry
pradipchm/mdanalysis
MDAnalysis is a Python library to analyze molecular dynamics simulations.
pradipchm/mdtraj
An open library for the analysis of molecular dynamics trajectories
pradipchm/ML-Notebooks
:fire: Machine Learning Notebooks
pradipchm/mlcolvar
A unified framework for machine learning collective variables for enhanced sampling simulations
pradipchm/mlreview_notebooks
Jupyter notebooks for "A high-bias, low-variance introduction to Machine Learning for physicists"
pradipchm/MolecularNodes
Toolbox for molecular animations in Blender, powererd by Geometry Nodes.
pradipchm/practical_cheminformatics_tutorials
Practical Cheminformatics Tutorials
pradipchm/pradipchm.github.io
Minimal Mistakes GitHub Pages site starter.
pradipchm/pymatgen
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.
pradipchm/pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
pradipchm/solvation-parameterization
pradipchm/SuperCellGenerator
Tool for setting up molecular crystal super cell from cif files
pradipchm/useful_rdkit_utils
Some useful RDKit functions
pradipchm/valsson-group.github.io
Valsson Research Group at UNT - Website
pradipchm/workshop-july-2022
Deep Modeling for Molecular Simulation, two-day virtual workshop, July 7-8, 2022
pradipchm/WorkshopMDMLEdinburgh2022