High-Performance Symbolic Regression in Python and Julia
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Updated
Jan 10, 2025 - Python
High-Performance Symbolic Regression in Python and Julia
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
Symbolic Geometric Algebra/Calculus package for SymPy 🔮
Functional tensors for probabilistic programming
A python framework for symbolic music generation, evaluation and analysis
SEMA is based on angr, a symbolic execution engine used to extract API calls. Especially, we extend ANGR with strategies to create representative signatures based on System Call Dependency graph (SCDG). Those SCDGs can be exploited in machine learning modules to do classification/detection.
A Python package for automata theory.
Specify and synthesize systems using symbolic algorithms
Simple swig bindings for the GNU Linear Programming Kit
Counterfactual Reasoning VQA Dataset
Real Spherical Harmonics for PyTorch
Symbolic Geometric Algebra with E-Graphs
Symbolic function approximator aims to generate a function using a genetic algorithm to approximate a data distribution using the symbolic paradigm with programming logic.
Synthetic data generation for evaluating Large Language Models reasoning.
Python symbolic canonicalizer and C code generator for embedding convex optimization problems.
Yet Another Analytical Inverse Kinematics Generator
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