A PyTorch Library for Accelerating 3D Deep Learning Research
- pytorch
- 3d-deep-learning
- neural-networks
- differentiable-rendering
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A PyTorch Library for Accelerating 3D Deep Learning Research
Official repository for the Boltz biomolecular interaction models
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
Message Passing Neural Networks for Molecule Property Prediction
Chai-1, SOTA model for biomolecular structure prediction
A set of documented functions for simulating the performance of photovoltaic energy systems.
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
Fast NumPy array functions written in C
3D medical imaging reconstruction software
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Interactive network visualization in Python and Dash, powered by Cytoscape.js
⚗ A package useful for chemistry written in Python
A Free and Open Source Python Library for Multiobjective Optimization
Simulate Functional Mock-up Units (FMUs) in Python
The open source air traffic simulator
Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)
Sequential regulatory activity predictions with deep convolutional neural networks.
Python-centric Cookiecutter for Molecular Computational Chemistry Packages
A High-Level Abstraction Framework for Quantum Algorithms
A generic interface for the environmental perception of automated driving functions in virtual scenarios.
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.