Zobrazeno 1 - 10
of 10
pro vyhledávání: '"William H Beluch"'
Autor:
João PL Castro, Michelle N Yancoskie, Marta Marchini, Stefanie Belohlavy, Layla Hiramatsu, Marek Kučka, William H Beluch, Ronald Naumann, Isabella Skuplik, John Cobb, Nicholas H Barton, Campbell Rolian, Yingguang Frank Chan
Publikováno v:
eLife, Vol 8 (2019)
Evolutionary studies are often limited by missing data that are critical to understanding the history of selection. Selection experiments, which reproduce rapid evolution under controlled conditions, are excellent tools to study how genomes evolve un
Externí odkaz:
https://doaj.org/article/3e7e931bf8674a47bc9d21c67150cb5f
Autor:
Adriana-Eliza Cozma, Kanil Patel, Bin Yang, Kilian Rambach, Michael Pfeiffer, William H. Beluch
Publikováno v:
2021 IEEE Radar Conference (RadarConf21).
Deep learning (DL) has recently attracted increasing interest to improve object type classification for automotive radar.In addition to high accuracy, it is crucial for decision making in autonomous vehicles to evaluate the reliability of the predict
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f05876c6e96000bd64b46d498fe3a4db
https://doi.org/10.1109/radarconf2147009.2021.9455269
https://doi.org/10.1109/radarconf2147009.2021.9455269
Publikováno v:
ICPR
Uncertainty estimates help to identify ambiguous, novel, or anomalous inputs, but the reliable quantification of uncertainty has proven to be challenging for modern deep networks. In order to improve uncertainty estimation, we propose On-Manifold Adv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d950cc8f6b33b755ba916e04331014a
https://doi.org/10.1109/icpr48806.2021.9413010
https://doi.org/10.1109/icpr48806.2021.9413010
Publikováno v:
G3: Genes, Genomes, Genetics
G3: Genes|Genomes|Genetics
G3: Genes|Genomes|Genetics
Most phenotypic traits in nature involve the collective action of many genes. Traits that evolve repeatedly are particularly useful for understanding how selection may act on changing trait values. In mice, large body size has evolved repeatedly on i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81db16f28583c9d1020d1ca7827f20bc
https://hdl.handle.net/21.11116/0000-0009-1FE5-321.11116/0000-0009-1FE7-1
https://hdl.handle.net/21.11116/0000-0009-1FE5-321.11116/0000-0009-1FE7-1
Most traits in nature involve the collective action of many genes. Traits that evolve repeatedly are particularly revealing about how selection may act on traits. In mice, large body size has evolved repeatedly on islands and under artificial selecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c812904a2347fbaff2d069616437430
https://doi.org/10.1101/747097
https://doi.org/10.1101/747097
Autor:
William H. Beluch, Campbell Rolian, Stefanie Belohlavy, Marek Kučka, Marta Marchini, Nicholas H. Barton, John Cobb, Michelle N. Yancoskie, Yingguang Frank Chan, Ronald Naumann, Layla Hiramatsu, Joao P. L. Castro, Isabella Skuplik
Publikováno v:
eLife, Vol 8 (2019)
eLife
eLife
Evolutionary studies are often limited by missing data that are critical to understanding the history of selection. Selection experiments, which reproduce rapid evolution under controlled conditions, are excellent tools to study how genomes evolve un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a0f91413032efb23e070ac1265eafde
https://elifesciences.org/articles/42014
https://elifesciences.org/articles/42014
Autor:
Isabella Skuplik, Stefanie Belohlavy, Marek Kučka, Campbell Rolian, Nicholas H. Barton, John Cobb, Ronald Naumann, Layla Hiramatsu, William H. Beluch, Joao P. L. Castro, Yingguang Frank Chan, Michelle N. Yancoskie, Marta Marchini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37e12a18c99bb476bf1e78f7e5e795ac
https://doi.org/10.7554/elife.42014.049
https://doi.org/10.7554/elife.42014.049
Autor:
João L. P. Castro, Michelle N. Yancoskie, John Cobb, Marta Marchini, Nicholas H. Barton, Stefanie Belohlavy, Marek Kučka, Ronald Naumann, Yingguang Frank Chan, Campbell Rolian, William H. Beluch, Isabella Skuplik
Evolutionary studies are often limited by missing data that are critical to understanding the history of selection. Selection experiments, which reproduce rapid evolution under controlled conditions, are excellent tools to study how genomes evolve un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b73e5c8fb471f4389295b00a046926e6
Publikováno v:
CVPR
Deep learning methods have become the de-facto standard for challenging image processing tasks such as image classification. One major hurdle of deep learning approaches is that large sets of labeled data are necessary, which can be prohibitively cos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9f28519de768780d003413bb1482f7f
https://doi.org/10.1109/cvpr.2018.00976
https://doi.org/10.1109/cvpr.2018.00976
Autor:
Lacey Sara Kaplan, Jayshree Shah, Genique Stanislaus, Jennifer Lynn Llanes, Melanie Marcincak, Miriam S Aioub, Diane Powell, Tarundeep Singh, Stuart L. Goldberg, William H. Beluch, Lissette Pajaro, Peggy Stone, Katarzyna Szyperek, Michele Hanrahan, Lynne Larsen, Jamie L Yaniga, Sandra Palomino, Elizabeth Jones, Sora Limor, Anita Vargas, Alyona Weinstein, Rebecca Hirsch, Kenneth Granholm
Publikováno v:
Blood. 118:4432-4432
Abstract 4432 Background: Although there have been tremendous improvements in the management of chronic myelogenous leukemia (CML), the success of treatment is dependent on adherence by the patient to oral tyrosine kinase inhibitor (tki) regimens in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3063d7cd29bd58756b0d24b98dc7b337
https://doi.org/10.1182/blood.v118.21.4432.4432
https://doi.org/10.1182/blood.v118.21.4432.4432