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Explore case studies in computational number theory, examining the interplay between computation and formalization in mathematical research and problem-solving.
Explore the intersection of visual reasoning and mathematical proofs, examining how diagrams enhance understanding and facilitate logical arguments in mathematics.
Explore post-rigorous mathematics and its formalization with Emily Riehl, delving into advanced concepts and their applications in modern mathematical research.
Explore natural theorem proving using Naproche-ZF, a powerful tool for formalizing mathematical proofs in a language close to human reasoning.
Explore innovative search interfaces tailored for mathematicians, enhancing research efficiency and knowledge discovery in mathematical domains.
Explore the role and challenges of LLMs/neural methods in autoformalisation, with insights on complementary symbolic approaches for parsing natural languages.
Explore autoformalisation techniques to transform informal mathematical proofs into rigorous, machine-verifiable formal proofs, enhancing theorem-proving capabilities.
Explore hypergraph rewriting as a computational foundation for diagrammatic calculus, covering various algebraic structures and featuring a Mathematica paclet implementation.
Explore Deligne's theorem in number theory, focusing on its formalization and implications for mathematical research and understanding.
Explore the cb-Bohnenblust-Hille inequality with constant one and its applications in quantum learning theory, including extensions to learning low-degree quantum objects.
Explore structure theorems in Boolean Function Analysis, including FKN theorem, Friedgut's junta theorem, and sharp threshold theorems, with focus on biased hypercube and symmetric group.
Explore signal recovery techniques using Fourier transforms and restriction theory. Delve into improved recovery conditions for multiple transmissions and continuous aspects of the problem.
Explore vector-valued concentration inequalities for the symmetric group, examining implications for Banach space geometry and building on recent advancements in discrete hypercube analysis.
Explore discrete functional inequalities as invariants for bi-Lipschitz embeddings, examining nonlinear type/cotype, convexity, and spectral gap to deduce nonembeddability results for various graphs.
Explore numerical modeling of vortex patterns in Bose-Einstein condensates using finite elements, focusing on mesh size requirements for accurate approximations of superfluid behavior.
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