Search Results for "linear program solver"
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Showing 13 open source projects for "linear program solver"
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1
POT
Python Optimal Transport
This open source Python library provides several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning. -
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The Operator Splitting QP Solver
The Operator Splitting QP Solver
OSQP uses a specialized ADMM-based first-order method with custom sparse linear algebra routines that exploit structure in problem data. The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust. -
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Poetiq
Reproduction of Poetiq's record-breaking submission to the ARC-AGI-1
...Instead of relying on a single prompt or fixed strategy, their solver dynamically adapts the reasoning path, selecting what to ask or analyze next depending on intermediate results — effectively compositing reasoning, perception, and program synthesis (or symbolic manipulation) in a loop. The repository allows others to reproduce their results, experiment with different LLM backends (e.g. the user may supply keys for supported models), and observe how their adaptive meta-system handles the logic and abstraction challenges. -
4
Sokoban Solver Statistics
Statistics for the best Sokoban solver programs
This project presents statistics for the best Sokoban solver programs. Additionally, it features a Sokoban program for playing the game. -
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5
PyTorch Implementation of SDE Solvers
Differentiable SDE solvers with GPU support and efficient sensitivity
...The program outputs figures to the path specified by <TRAIN_DIR>. Training should stabilize after 500 iterations with the default hyperparameters. examples/sde_gan.py learns an SDE as a GAN, as in [2], [3]. The example trains an SDE as the generator of a GAN, whilst using a neural CDE [4] as the discriminator. -
6
OpenOCL Matlab
Optimal control, trajectory optimization, model-predictive control.
The Open Optimal Control Library is a software framework in Matlab/Octave for modeling optimal control problem. It uses automatic differentiation and fast non-linear programming solvers. It implements direct methods. In the backend it uses CasADi and ipopt. -
7
Neural Libs
Neural network library for developers
This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network. -
8
SoMaTePs
Solver for Math Text Problems
The Word Problem Solver is a program that is able to solve math word problems like they are teached in the first four classes in primary school. Currenty the program is restricted to math word problems that are presented in german language. -
9
mouse-solver
CDCL Satisfiability Solvers written in F#
an educational logic program solver for exploring entry-level concepts in satisfiability solving such as 1st UIP, learned clauses, backjumping, etc. -
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10
Linear Regression
linear regression along with plotting
Linear regression with plotting facility for simple and 2d regression. linear_regression.c is the main file and Include the library lib_sim_eq.c. You must have installed gnuplot prior to compiling the program. -
11
This is a continuation of the FreeCell Java Solver, because I was not able to access my original account anymore (likely due to sourceforge glitches), and I need to make updates to the program.
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12
VKAS - a genetic function finder
An AI program that deploys genetic programming
...If a suitable answer is not found then the program stops after specified max generations are over. -
13
Cigol (logic, spelled backwards) is a deductive logic solver. It can be embedded inside a parent program or used from the command line. It has absolutely no relationship to Tom Mitchell's book on Machine Learning.
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