Transforms complex documents like PDFs into LLM-ready markdown/JSON for your Agentic workflows.

DSPy: The framework for programming—not prompting—language models

Agent Laboratory is an end-to-end autonomous research workflow meant to assist you as the human researcher toward implementing your research ideas

Hierarchical Reasoning Model Official Release

(NeurIPS 2022) Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination

MatterSim: A deep learning atomistic model across elements, temperatures and pressures.

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.

A python script to solve the Cahn-Hilliard equation using an implicit pseudospectral method

Matlab codes from the book Introduction to Mechanics of Solids, Oxford University Press (2022) by Lallit Anand, Ken Kamrin, and Sanjay Govindjee; and Matlab codes from the companion problems book, …

Lecture notes and code for the course PHYS6350 Computational Physics at the University of Houston

LLMs as Copilots for Theorem Proving in Lean

A julia package to either fit the parameters of a specified equivalent electrical circuit to electrochemical impedance data, or to suggest a plausible circuit configuration for a given set of measu…

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

Complex tensor and complex functions for pytorch.

🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

Hierarchical Bayesian methods for inversion of electrochemical impedance spectroscopy (EIS) data

Retrieve author and publication information from Google Scholar in a friendly, Pythonic way without having to worry about CAPTCHAs!

Collection of different algorithms for calculating impedance distribution of relaxation time

This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a community of users and contributors by focusing initially o…

A differentiable PDE solving framework for machine learning

codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"

Fast and Easy Infinite Neural Networks in Python

Python model for constrained GP