Robot | Path | Permission |
GoogleBot | / | ✔ |
BingBot | / | ✔ |
BaiduSpider | / | ✔ |
YandexBot | / | ✔ |
Title | RoboNet |
Description | Abstract Code and Sundry Featured Robots By the Numbers Contribute RoboNet Sudeep Dasari 1,4 , Frederik Ebert 1 , Stephen Tian 1 , Suraj Nair 2 , Bernadet |
Keywords | N/A |
WebSite | robonet.wiki |
Host IP | 185.199.108.153 |
Location | - |
Site | Rank |
US$1,253,355
Last updated: 2023-05-18 19:15:36
robonet.wiki has Semrush global rank of 8,444,783. robonet.wiki has an estimated worth of US$ 1,253,355, based on its estimated Ads revenue. robonet.wiki receives approximately 144,618 unique visitors each day. Its web server is located in -, with IP address 185.199.108.153. According to SiteAdvisor, robonet.wiki is safe to visit. |
Purchase/Sale Value | US$1,253,355 |
Daily Ads Revenue | US$1,157 |
Monthly Ads Revenue | US$34,709 |
Yearly Ads Revenue | US$416,500 |
Daily Unique Visitors | 9,642 |
Note: All traffic and earnings values are estimates. |
Host | Type | TTL | Data |
robonet.wiki. | A | 3599 | IP: 185.199.108.153 |
robonet.wiki. | A | 3599 | IP: 185.199.111.153 |
robonet.wiki. | A | 3599 | IP: 185.199.110.153 |
robonet.wiki. | A | 3599 | IP: 185.199.109.153 |
robonet.wiki. | NS | 21600 | NS Record: ns-cloud-e2.googledomains.com. |
robonet.wiki. | NS | 21600 | NS Record: ns-cloud-e4.googledomains.com. |
robonet.wiki. | NS | 21600 | NS Record: ns-cloud-e1.googledomains.com. |
robonet.wiki. | NS | 21600 | NS Record: ns-cloud-e3.googledomains.com. |
Abstract Code and Sundry Featured Robots By the Numbers Contribute RoboNet Sudeep Dasari 1,4 , Frederik Ebert 1 , Stephen Tian 1 , Suraj Nair 2 , Bernadette Bucher 3 , Karl Schmeckpeper 3 , Siddharth Singh 3 , Sergey Levine 1 , Chelsea Finn 2 UC Berkeley 1 , Stanford University 2 , University of Pennsylvania 3 , CMU 4 Find Out More Abstract Robot learning has emerged as a promising tool for taming the complexity and diversity of the real world. Methods based on high-capacity models, such as deep networks, hold the promise of providing effective generalization to a wide range of open-world environments. However, these same methods typically require large amounts of diverse training data to generalize effectively. In contrast, most robotic learning experiments are small-scale, single-domain, and single-robot. This leads to a frequent tension in robotic learning: how can we learn generalizable robotic controllers without having to collect impractically large amounts of data for each |
HTTP/1.1 301 Moved Permanently Server: GitHub.com Content-Type: text/html Location: https://www.robonet.wiki/ X-GitHub-Request-Id: CEC6:DF85:55F59E:5CBB82:62D27AD3 Content-Length: 162 Accept-Ranges: bytes Date: Sat, 16 Jul 2022 08:46:12 GMT Via: 1.1 varnish Age: 0 Connection: keep-alive X-Served-By: cache-hel1410022-HEL X-Cache: MISS X-Cache-Hits: 0 X-Timer: S1657961172.958373,VS0,VE110 Vary: Accept-Encoding X-Fastly-Request-ID: 18ab5a1b4c21ba88a704e7e69989460c5c48b37a HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Fri, 25 Oct 2019 02:13:12 GMT access-control-allow-origin: * etag: "5db25a38-353f" expires: Sat, 16 Jul 2022 08:56:12 GMT cache-control: max-age=600 x-proxy-cache: MISS x-github-request-id: 6716:1587:B36832:BC68F8:62D27AD4 accept-ranges: bytes date: Sat, 16 Jul 2022 08:46:12 GMT via: 1.1 varnish age: 0 x-served-by: cache-hel1410021-HEL x-cache: MISS x-cache-hits: 0 x-timer: S1657961172.149399,VS0,VE118 vary: Accept-Encoding x-fastly-request-id: 54b1f43c33cfd0b501c8713f52c1df29fdb709b8 content-length: 13631 |