Artificial Intelligence (ChatGPT) and Bloom’s Taxonomy in Theoretical Computer Science Education by Hashim Habiballa, Martin Kotyrba, Eva Volna, Vladimir Bradac, Martin Dusek

“…The study focuses on evaluating the performance of AI-based tools, specifically ChatGPT versions 3.5 and 4.0, in comparison to human students in the field of Theoretical Computer Science Education. The experiment aims to assess the capabilities of both AI and human subjects in solving learning tasks based on Bloom’s Taxonomy. …”
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The Boolean zeta function by Algirdas Javtokas

“…., xm) function known in theoretical computer science. …”
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Author Correction: A simple model for Behavioral Time Scale Synaptic Plasticity (BTSP) provides content addressable memory with binary synapses and one-shot learning by Yujie Wu, Wolfgang Maass

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Collapsing along monotone poset maps by Dmitry N. Kozlov

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A Unif: A common supercategory of pMET and Unif by R. Lowen, B. Windels

“…Some natural examples are presented, such as function spaces, hyperspaces, spaces of measures, and an example concerning theoretical computer science.…”
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Computation and Calculus for Combinatorial Geometric Series and Binomial Identities and Expansions by Chinnaraji Annamalai

“…Combinatorics involves integers, factorials, binomial coefficients, discrete mathematics, and theoretical computer science for finding solutions to the problems in computing and engineering science. …”
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The Principle of Mathematical Induction: Applications in Physical Optics by Joseph Ivin Thomas

“…In the contemporary university milieu, the demonstrative scheme is taught as part of a course in discrete mathematics, set theory, number theory, graph theory, group theory, game theory, linear algebra, logic, and combinatorics. In theoretical computer science, it bears the pivotal role of developing the appropriate cognitive skills necessary for the effective design and implementation of algorithms, assessing for both their correctness and complexity. …”
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A simple model for Behavioral Time Scale Synaptic Plasticity (BTSP) provides content addressable memory with binary synapses and one-shot learning by Yujie Wu, Wolfgang Maass

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Hyperbolic Metric Spaces and Stochastic Embeddings by Chris Gartland

“…Stochastic embeddings of finite metric spaces into graph-theoretic trees have proven to be a vital tool for constructing approximation algorithms in theoretical computer science. In the present work, we build out some of the basic theory of stochastic embeddings in the infinite setting with an aim toward applications to Lipschitz free space theory. …”
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Topology-Aware Bus Routing in Complex Networks of Very-Large-Scale Integration with Nonuniform Track Configurations and Obstacles by Ziran Zhu, Zhipeng Huang, Jianli Chen, Longkun Guo

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Diagnosis of planktonic trophic network dynamics with sharp qualitative changes by Gaucherel, Cedric, Fayolle, Stolian, Savelli, Raphael, Philippine, Olivier, Pommereau, Franck, Dupuy, Christine

“…Applying discrete-event models from theoretical computer science, a mechanistic and qualitative model was developed that allowed computation of the exhaustive dynamics of a given trophic network and its environment. …”
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