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Explores localization properties of Schrödinger semigroups associated with sub-Laplacians, presenting mathematical insights and techniques in the field of partial differential equations and harmonic analysis.
Explores sharp quantitative stability of Poincaré-Sobolev inequality, presenting mathematical insights and advancements in this area of analysis. Contributes to ongoing research in functional inequalities.
Explores boundary-value problems for linear loaded integro-differential equations, discussing mathematical techniques and applications in theoretical physics and engineering.
Explore residues and trace maps in Grothendieck Duality, advancing understanding of algebraic geometry and commutative algebra concepts within the broader context of dualities in topology and algebra.
Explore advanced concepts in algebraic topology, focusing on ambidexterity and its applications in duality phenomena within tensor-triangulated categories.
Explore Quillen Stratification Theorems in algebraic topology, examining their applications and implications for understanding cohomological support varieties and triangulated categories.
Explore weak lensing techniques without shape noise in cosmological surveys. Learn advanced methods for analyzing large-scale structure data and improving precision in cosmological measurements.
Explore galaxy formation during cosmic reionization and its impact on large-scale structures. Gain insights into early universe dynamics and the evolution of cosmic structures.
Explore Bayesian field-level inference techniques for weak lensing data analysis in cosmology. Learn advanced methods to extract valuable information from large-scale structure surveys.
Explores small scale formations in incompressible Boussinesq equations, discussing mathematical insights and implications for fluid dynamics and atmospheric sciences.
Explore non-Archimedean Second Main Theorems and their applications in this lecture by Ta Thi Hoai An, part of the inaugural meeting of Asian-Oceanian Women in Mathematics.
Explore topological invariants in geometry with Jaya N Iyer. This talk delves into advanced mathematical concepts, offering insights for researchers and enthusiasts in the field.
Explore data-driven approaches in cosmology, leveraging statistical methods and machine learning to analyze vast datasets and uncover insights about the universe's structure and evolution.
Explore advanced neural simulation-based inference techniques for high energy physics, focusing on applications in data analysis and new physics discovery at particle colliders.
Explore neural simulation-based inference techniques for high energy physics, focusing on advanced machine learning applications in data analysis and new physics discovery.
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