End-to-end imitation learning of lane following policies using sum-product networks (2019)
- Authors:
- USP affiliated authors: MAUÁ, DENIS DERATANI - IME ; GEH, RENATO LUI - IME
- Unidade: IME
- DOI: 10.5753/eniac.2019.9292
- Subjects: INTELIGÊNCIA ARTIFICIAL; APRENDIZAGEM PROFUNDA
- Keywords: intelligent robotics
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2019
- Source:
- Título do periódico: Anais
- Conference titles: Brazilian Conference on Intelligent Systems - BRACIS
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
-
ABNT
GEH, Renato Lui e MAUÁ, Denis Deratani. End-to-end imitation learning of lane following policies using sum-product networks. 2019, Anais.. Porto Alegre: SBC, 2019. Disponível em: https://doi.org/10.5753/eniac.2019.9292. Acesso em: 28 abr. 2024. -
APA
Geh, R. L., & Mauá, D. D. (2019). End-to-end imitation learning of lane following policies using sum-product networks. In Anais. Porto Alegre: SBC. doi:10.5753/eniac.2019.9292 -
NLM
Geh RL, Mauá DD. End-to-end imitation learning of lane following policies using sum-product networks [Internet]. Anais. 2019 ;[citado 2024 abr. 28 ] Available from: https://doi.org/10.5753/eniac.2019.9292 -
Vancouver
Geh RL, Mauá DD. End-to-end imitation learning of lane following policies using sum-product networks [Internet]. Anais. 2019 ;[citado 2024 abr. 28 ] Available from: https://doi.org/10.5753/eniac.2019.9292 - Scalable learning of probabilistic circuits
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Informações sobre o DOI: 10.5753/eniac.2019.9292 (Fonte: oaDOI API)
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