FiPy is a Finite Volume PDE solver written in Python
- scientific-computing
- scientific-computing-with-python
- phase-field
- materials-science
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FiPy is a Finite Volume PDE solver written in Python
Spatial Single Cell Analysis in Python
Aioresponses is a helper for mock/fake web requests in python aiohttp package.
The official bitbake Git is at https://git.openembedded.org/bitbake/. Do not open issues or file pull requests here.
A Euclidean diffusion model for structure-based drug design.
A tool for semi-automatic cell type classification
:sound: spafe: Simplified Python Audio Features Extraction
Sequential regulatory activity predictions with deep convolutional neural networks.
An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.)
A High-Level Abstraction Framework for Quantum Algorithms
💃 Free CC0 mannequin pose reference library for AI image tools (Nano Banana, ChatGPT, ComfyUI, Midjourney) — 250+ poses × 5 angles in line art, names in ja/zh/en/ko
Upload once to create multiple, relative PRs. Productivity-focused git tools with patch revision tracking, rebase detection and more. Uses python and git plumbing commands.
Quantum Computer Library for Everyone
The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)
Wraps any WSGI application and makes it easy to send test requests to that application, without starting up an HTTP server.
Python's missing "algorave" module. Live code music with Python using MIDI, OSC and/or SuperCollider.
a socket mock framework - for all kinds of socket animals, web-clients included
A Python module for time-frequency analysis
RNA-seq prediction with deep convolutional neural networks.
Bi-Directional Equivariant Long-Range DNA Sequence Modeling
Neural machine translation between the writings of Shakespeare and modern English using TensorFlow
Statistical NLG for spoken dialogue systems
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524