Like `requests` for mathematical computing, making complex math feel simple.
Tools for using computer algebra systems to solve math problems step-by-step with reinforcement learning
[NeurIPS 2023] This is the official code for the paper "TPSR: Transformer-based Planning for Symbolic Regression"
❓y0 (pronounced "why not?") is for causal inference in Python
Tools for the symbolic manipulation of PyMC models, Theano, and TensorFlow graphs.
[ICLR 2024 Spotlight] This is the official code for the paper "SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training"
Ensembler is a python package that provides fast and easy access to 1D and 2D model system simulations. It can be used for method development or to deepen understanding of a broad spectrum of modeling methods, from basic sampling techniques to enhanced sampling and free energy calculations. It is easy to install, fast, increases shareability, co…
Combining Symbolic and Function Evaluation Expressions In Neural Programs
Symbolic calculus for partial differential equations (and variational forms)
Symbolic Geometric Algebra with E-Graphs
Code and data for the paper "Pretrained Language Models are Symbolic Mathematics Solvers too!", arXiv:2110.03501
A symbolic math toolbox in Python to explore the design space of analog circuits. Find possible filters for any given nodal equation set and allowed impedance connections. Size, symbolically or with SPICE, for a given response using Bayesian optimization or Evolutionary algorithms.
Calculation of the trajectory of a spinning particle around a black hole with an arbitrary metric tensor.
A modular, configurable LLM middleware pipeline that transforms raw prompts into enterprise-ready microservices.
A Scientific Calculator with Graphing and advanced mathematical calculation capabilities
Intuitive symbolic interface for constrained optimization problems. Write natural Python, get automatic gradients and solvers.
A Python toolkit for advanced mathematics in AI and computational neuroscience, designed to support the development of the Fully Unified Model (FUM).
A Symbolic Library for finding Laplace transforms for provided mathematical expressions.
Python library for calculating formulas for derivatives.
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