Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Christoph-Nikolas Straehle"'
Publikováno v:
ITSC
Imitation learning on real-world data has the potential to improve the simulation of real-world traffic. However, learning from human demonstrations can be challenging since the recorded behavior is typically noisy and multimodal. Most policies used
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89701246acf9484f16d0435f8355cb2f
https://doi.org/10.1109/itsc48978.2021.9564456
https://doi.org/10.1109/itsc48978.2021.9564456
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030712778
GCPR
GCPR
Prediction of trajectories such as that of pedestrians is crucial to the performance of autonomous agents. While previous works have leveraged conditional generative models like GANs and VAEs for learning the likely future trajectories, accurately mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52c4177f9c730a218aefae94aa205add
https://doi.org/10.1007/978-3-030-71278-5_20
https://doi.org/10.1007/978-3-030-71278-5_20
Autor:
Patricia Iglesias Sánchez, Arvind Kumar Shekar, Christoph-Nikolas Straehle, Emmanuel Müller, Tom Bocklisch
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783319712482
ECML/PKDD (1)
ECML/PKDD (1)
Feature ranking is beneficial to gain knowledge and to identify the relevant features from a high-dimensional dataset. However, in several datasets, few features by itself might have small correlation with the target classes, but by combining these f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2181575cb70962e6f6a5aa7e7156883
https://doi.org/10.1007/978-3-319-71249-9_15
https://doi.org/10.1007/978-3-319-71249-9_15