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.
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The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
- automatic-differentiation
- aad
- algorithmic-differentiation
- autodiff
Universal cheminformatics toolkit, utilities and database search tools
- indigo
- bingo
- cheminformatics
- chemistry
C++ ODBC wrapper
- odbc
- database-access
- database-access-library
- odbc-api
Modern C++ ORM library
TOra is an open source SQL IDE for Oracle, MySQL and PostgreSQL dbs
Small C++ header to display async animations, counters, progress bars, and status messages
- cpp
- progress-bar
- counter
- animation
Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight
- robotics
- quadrotor
- trajectory-optimization
- motion-planning
Intel Iris Xe (Raptor Lake) Metal acceleration on macOS Tahoe — Dell XPS 13 Plus 9320 OpenCore hackintosh. Work in progress.
- hackintosh
- intel-gpu
- iris-xe
- macos-tahoe
Daggy - Data Aggregation Utility and C/C++ developer library for data streams catching
- serverless-framework
- streaming
- stream-processing
- qt
Multi-core Window-Based Stream Processing Engine
- llvm
- incremental-computation
- aggregation
- stream-processing
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
- svm
- regression
- classification
- machine-learning