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Title | Home | |
Description | deluca Performant, differentiable reinforcement |
Keywords | N/A |
WebSite | deluca.fyi |
Host IP | 185.199.110.153 |
Location | - |
Site | Rank |
US$309,887
Last updated: 2023-05-18 00:16:51
deluca.fyi has Semrush global rank of 34,155,467. deluca.fyi has an estimated worth of US$ 309,887, based on its estimated Ads revenue. deluca.fyi receives approximately 35,757 unique visitors each day. Its web server is located in -, with IP address 185.199.110.153. According to SiteAdvisor, deluca.fyi is safe to visit. |
Purchase/Sale Value | US$309,887 |
Daily Ads Revenue | US$287 |
Monthly Ads Revenue | US$8,582 |
Yearly Ads Revenue | US$102,978 |
Daily Unique Visitors | 2,384 |
Note: All traffic and earnings values are estimates. |
Host | Type | TTL | Data |
deluca.fyi. | A | 3600 | IP: 185.199.110.153 |
deluca.fyi. | A | 3600 | IP: 185.199.111.153 |
deluca.fyi. | A | 3600 | IP: 185.199.108.153 |
deluca.fyi. | A | 3600 | IP: 185.199.109.153 |
deluca.fyi. | NS | 21600 | NS Record: ns-cloud-a2.googledomains.com. |
deluca.fyi. | NS | 21600 | NS Record: ns-cloud-a1.googledomains.com. |
deluca.fyi. | NS | 21600 | NS Record: ns-cloud-a3.googledomains.com. |
deluca.fyi. | NS | 21600 | NS Record: ns-cloud-a4.googledomains.com. |
deluca Performant, differentiable reinforcement learning View the Project on GitHub google/deluca Reinforcement learning with derivatives deluca is a jax -based library that provides differentiable environments, control algorithms that take advantage of such environments, and benchmarking tools. This software is currently in alpha and is changing rapidly. We have a paper describing the library available here . Getting started deluca is a Python library that can be installed via pip install deluca . Example notebooks We maintain a number of Jupyter notebooks and will continue to add more: A Regret Minimization Approach to Iterative Learning Control ( paper , code ) Machine Learning for Mechanical Ventilation Control ( paper , code ) Example without derivatives import jax from deluca.envs import Reacher from deluca.agents import Random env = Reacher . create () env_state = env . init () agent = Random . create ( func = lambda key : jax . random . uniform ( key , ( env . action_dim ,))) |
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