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of 114
pro vyhledávání: '"John Lafferty"'
Publikováno v:
eLife, Vol 11 (2022)
Animals have evolved sophisticated visual circuits to solve a vital inference problem: detecting whether or not a visual signal corresponds to an object on a collision course. Such events are detected by specific circuits sensitive to visual looming,
Externí odkaz:
https://doaj.org/article/31ce186ffbec459389e880a7bf0a006e
Publikováno v:
Journal of Vision. 22:4308
Publikováno v:
eLife, Vol 11 (2022)
Animals have evolved sophisticated visual circuits to solve a vital inference problem: detecting whether or not a visual signal corresponds to an object on a collision course. Such events are detected by specific circuits sensitive to visual looming,
Autor:
John Lafferty, Michihiro Yasunaga
Publikováno v:
AAAI
Scientific documents rely on both mathematics and text to communicate ideas. Inspired by the topical correspondence between mathematical equations and word contexts observed in scientific texts, we propose a novel topic model that jointly generates m
Publikováno v:
AIAA Scitech 2021 Forum.
Autor:
Laura E. Dogariu, Richard B. Miles, Michael S. Smith, John Lafferty, Arthur Dogariu, Brianne Macmanamen
Publikováno v:
AIAA Scitech 2021 Forum.
Publikováno v:
AIAA Scitech 2020 Forum.
Publikováno v:
ASPLOS
Many modern computing systems must provide reliable latency with minimal energy. Two central challenges arise when allocating system resources to meet these conflicting goals: (1) complexity modern hardware exposes diverse resources with complicated
Autor:
ChengXiang Zhai, John Lafferty
Publikováno v:
SIGIR
We present a framework for information retrieval that combines document models and query models using a probabilistic ranking function based on Bayesian decision theory. The framework suggests an operational retrieval model that extends recent develo