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Title | Probabilistic Models of Cognition - 2nd |
Description | ☰ Home Introduction Generative models Conditioning Causal and statistical dependence Conditional dependence Social cognition Interlude - Bayesian data ana |
Keywords | N/A |
WebSite | probmods.org |
Host IP | 172.67.199.155 |
Location | United States |
Site | Rank |
US$3,700,702
Last updated: 2023-05-10 01:54:23
probmods.org has Semrush global rank of 2,860,080. probmods.org has an estimated worth of US$ 3,700,702, based on its estimated Ads revenue. probmods.org receives approximately 427,005 unique visitors each day. Its web server is located in United States, with IP address 172.67.199.155. According to SiteAdvisor, probmods.org is safe to visit. |
Purchase/Sale Value | US$3,700,702 |
Daily Ads Revenue | US$3,417 |
Monthly Ads Revenue | US$102,481 |
Yearly Ads Revenue | US$1,229,772 |
Daily Unique Visitors | 28,467 |
Note: All traffic and earnings values are estimates. |
Host | Type | TTL | Data |
probmods.org. | A | 300 | IP: 172.67.199.155 |
probmods.org. | A | 300 | IP: 104.21.36.210 |
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probmods.org. | AAAA | 300 | IPV6: 2606:4700:3033::6815:24d2 |
probmods.org. | NS | 86400 | NS Record: sam.ns.cloudflare.com. |
probmods.org. | NS | 86400 | NS Record: adel.ns.cloudflare.com. |
probmods.org. | MX | 300 | MX Record: 10 mail.probmods.org. |
☰ Home Introduction Generative models Conditioning Causal and statistical dependence Conditional dependence Social cognition Interlude - Bayesian data analysis Interlude - Algorithms for inference Rational process models Learning as conditional inference Learning with a language of thought Hierarchical models Occam’s Razor Mixture models Learning (deep) continuous functions Appendix - JavaScript basics Appendix - Useful distributions Probabilistic Models of Cognition by Noah D. Goodman, Joshua B. Tenenbaum & The ProbMods Contributors This book explores the probabilistic approach to cognitive science, which models learning and reasoning as inference in complex probabilistic models. We examine how a broad range of empirical phenomena, including intuitive physics, concept learning, causal reasoning, social cognition, and language understanding, can be modeled using probabilistic programs (using the WebPPL language). Contributors This book is an open source project. We welcome content |
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