Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Serim Ryou"'
Autor:
Jennifer J. Sun, Serim Ryou, Roni H. Goldshmid, Brandon Weissbourd, John O. Dabiri, David J. Anderson, Ann Kennedy, Yisong Yue, Pietro Perona
Publikováno v:
Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit
We propose a method for learning the posture and structure of agents from unlabelled behavioral videos. Starting from the observation that behaving agents are generally the main sources of movement in behavioral videos, our method, Behavioral Keypoin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32b5f01cd03fba18950d874f7b6a0026
http://arxiv.org/abs/2112.05121
http://arxiv.org/abs/2112.05121
Autor:
Serim Ryou, Sarah E. Reisman, Michael R. Maser, Yisong Yue, Alexander Y. Cui, Travis J. DeLano
Publikováno v:
Journal of chemical information and modeling. 61(1)
Machine-learned ranking models have been developed for the prediction of substrate-specific cross-coupling reaction conditions. Data sets of published reactions were curated for Suzuki, Negishi, and C-N couplings, as well as Pauson-Khand reactions. S
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73b1e9bf955e916dbb25aae6a1792a25
https://pubmed.ncbi.nlm.nih.gov/33417449
https://pubmed.ncbi.nlm.nih.gov/33417449
Autor:
Serim Ryou, Alexander Y. Cui, Michael R. Maser, Sarah E. Reisman, Yisong Yue, Travis J. DeLano
Machine-learned ranking models have been developed for the prediction of substrate-specific cross-coupling reaction conditions. Datasets of published reactions were curated for Suzuki, Negishi, and C–N couplings, as well as Pauson–Khand reactions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c8458d53e1645f9bbecf743ca6c8ea7
https://doi.org/10.26434/chemrxiv.13087769.v1
https://doi.org/10.26434/chemrxiv.13087769.v1
Machine-learned ranking models have been developed for the prediction of substrate-specific cross-coupling reaction conditions. Datasets of published reactions were curated for Suzuki, Negishi, and C–N couplings, as well as Pauson–Khand reactions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d43c187f3e6f960fc8ec31a3bc33dc99
https://doi.org/10.26434/chemrxiv.13087769
https://doi.org/10.26434/chemrxiv.13087769
Publikováno v:
ICCV
We propose a novel loss function that dynamically rescales the cross entropy based on prediction difficulty regarding a sample. Deep neural network architectures in image classification tasks struggle to disambiguate visually similar objects. Likewis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04e61c299853fb019ce97eb7a67e5d5f
https://doi.org/10.1109/iccv.2019.00609
https://doi.org/10.1109/iccv.2019.00609