NVlabs/RL-TNCO
RL-TNCO: A reinforcement learning algorithm for solving the tensor network contraction problem
This project helps researchers and engineers who work with tensor networks by efficiently finding the best contraction order for complex tensor operations. You input a description of your tensor network (equations, shapes, and index sizes), and it outputs a highly optimized contraction path and its computational cost. This tool is designed for specialists in fields requiring large-scale tensor computations, such as quantum physics, machine learning, or signal processing.
No commits in the last 6 months.
Use this if you need to optimize the performance of complex tensor network computations to reduce processing time and resource usage.
Not ideal if you are new to tensor networks or reinforcement learning and need a basic introduction rather than an optimization tool.
Stars
10
Forks
1
Language
Python
License
—
Category
Last pushed
Mar 31, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/NVlabs/RL-TNCO"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DLR-RM/stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
google-deepmind/dm_control
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning...
Denys88/rl_games
RL implementations
pytorch/rl
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
yandexdataschool/Practical_RL
A course in reinforcement learning in the wild