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Explore a wide range of free and certified Graph theory online courses. Find the best Graph theory training programs and enhance your skills today!
Explore matroids and canonical forms, their theoretical foundations, and practical applications in algebraic topology and related fields.
Explore advancements in number theory since Fermat's Last Theorem, focusing on modularity and its impact on mathematical research over the past three decades.
Exploration of perfect bases in representation theory, examining three approaches and their combinatorial implications for tensor product multiplicities in semisimple groups.
Explores recent developments in prescribing mean curvature equations, focusing on existence theory, min-max theory for CMC/PMC surfaces, and Morse theory for area functional. Includes solution to Multiplicity One Conjecture.
Explores probability theory for random groups in number theory, topology, and combinatorics. Covers moment problems, universality theorems, and distributions of class groups and Selmer groups.
Explore algebraic-geometrical methods in integrable systems theory with renowned mathematician Igor Krichever, delving into advanced mathematical concepts and their applications.
Explore matroid theory's origins, connections, and recent geometric advances in combinatorial mathematics, highlighting matroid polytope, Bergman fan, and conormal fan models.
Recent advancements in stochastic distributed parameter control systems, focusing on controllability of hyperbolic equations and Pontryagin-type maximum principle for controlled stochastic evolution equations.
Explore connections between groups, manifolds, and graph limits in mathematics, uncovering fascinating relationships and applications in diverse areas of study.
Explore measurable graph combinatorics with Andrew Marks, delving into advanced mathematical concepts and their applications in this insightful lecture.
Explore homotopy patterns in group theory, delving into advanced mathematical concepts and their applications in topology and algebra.
Comprehensive exploration of density functional theory, covering advanced concepts and applications in materials science, presented by Prof. Vikram Gavini at IPAM's exascale mathematics workshop.
Comprehensive introduction to density functional theory, exploring its principles and applications in materials science and computational physics.
Explores Graph MLP-Mixer, a novel GNN architecture overcoming limitations in graph representation learning, offering improved long-range dependencies and efficiency for molecular analysis.
Explores techniques for explaining complex machine learning models, focusing on similarity, graph, and transformer structures. Discusses applications in knowledge evolution, gender bias, and task-solving.
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