A lean C++ library for working with point cloud data
- point-cloud
- icp
- ransac
- convex-hull
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A lean C++ library for working with point cloud data
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis
A coupling library and ecosystem for partitioned multi-physics and multi-scale simulations, including surface and volume coupling.
:spider_web: Gmsh for Python
Foundation Models for Genomics & Transcriptomics
C++ library for solving large sparse linear systems with algebraic multigrid method
Parallel solvers for sparse linear systems featuring multigrid methods.
A lightweight high performance tensor algebra framework for modern C++
An axiom-free formalization of category theory in Coq for personal study and practical work
In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
A Go package for engineering organisms.
VexCL is a C++ vector expression template library for OpenCL/CUDA/OpenMP
A flexible framework for solving PDEs with modern spectral methods.
RBDL is a C++ library that contains some essential and efficient rigid body dynamics algorithms such as the Articulated Body Algorithm (ABA) for forward dynamics, Recursive Newton-Euler Algorithm (RNEA) for inverse dynamics, the Composite Rigid Body Algorithm (CRBA) for the efficient computation of the joint space inertia matrix and is also able to compute forward dynamics with external contact constraints and collision impulses. Furthermore it has some basic support for forward and inverse kinematics.
Flutter weather application with beautiful UI and UX.
Algebraic Multigrid Solvers in Python
Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data
The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.
:spider_web: Mesh optimization, mesh smoothing.
Spatial Single Cell Analysis in Python
Model layer for Meteor
ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization.
🎯 A comprehensive gradient-free optimization framework written in Python