Incumbent
发表于 2025-3-28 16:22:28
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A保存的
发表于 2025-3-28 19:41:51
Steven D. Billings,Rajiv M. Patel If . is a full cartesian closed subcategory of ALG. such that . is closed under . → ., then every object . is ., i.e., im(.) is algebraic for all . ∃ .. This is equivalent to assuming that all order-dense chains in K(.) are degenerate. If . contains an isomorphic copy of the flat natural numbers, t
提名的名单
发表于 2025-3-29 02:21:53
Andrew L. Folpe If . is a full cartesian closed subcategory of ALG. such that . is closed under . → ., then every object . is ., i.e., im(.) is algebraic for all . ∃ .. This is equivalent to assuming that all order-dense chains in K(.) are degenerate. If . contains an isomorphic copy of the flat natural numbers, t
赞美者
发表于 2025-3-29 03:50:22
Darya Buehler,Rajiv M. Patel,Steven D. Billingsxploration trees to input exploration trees, respectively. We use the framework of ., a reformulation of a class of Kahn-Plotkin‘s concrete data structures. In sequential data structures, data are constructed by alternating questions and answers. Sequential data structures and symmetric algorithms a
正常
发表于 2025-3-29 08:24:38
Rajiv M. Patel,Reena Singh,Aaron M. Udager,Steven D. Billingsw paradigm for quantum computation beyond the usual quantum .This monograph provides a mathematical foundation to the theory of quantum information and computation, with applications to various open systems including nano and bio systems..It includes introductory material on algorithm, functional
promote
发表于 2025-3-29 13:29:10
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gospel
发表于 2025-3-29 19:28:24
Aaron M. Udager,Reena Singh,Steven D. Billings,Rajiv M. Patelatistical Mechanics. Continuous Systems" (Gordon & Breach SP, 1989) written together with my colleagues V. I. Gerasimenko and P. V. Malyshev. Taken together, these books give a complete pre sentation of the statistical mechanics of continuous systems, both quantum and classical, from the common poi
Gratulate
发表于 2025-3-29 22:57:48
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背带
发表于 2025-3-30 02:03:54
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Capitulate
发表于 2025-3-30 06:43:00
Steven D. Billings,Rajiv M. Patelices and incre- ingly common environment-embedded sensors are the primary generators of m- sive data sets. Being able to derive scienti?c insight from data increasingly depends on having mathematical and perceptual models to provide the necessary foundation for effective data analysis and comprehens