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Explore the potential of generalised divergences in enhancing invariant neural networks, examining their impact on network performance and robustness.
Explore PDE-G-CNNs: equivariant networks with geometric symmetries, data efficiency, and extendability. Discover their functional properties and applications in image processing and deep learning.
Explore Gibbs manifolds and their applications in optimization, statistics, and quantum physics, extending toric geometry concepts through an Algebraic Statistics lens.
Explore the Rankin-Cohen deformation quantization, its connections to modular forms and foliations, and discover a new oscillatory integral formula for Zagier's UDF.
Explore eigenvalues in Gordon Klein equation with Schwarzschild metric, examining implications for black hole information paradox and eternal black holes.
Explore geometric principles bridging classical and quantum mechanics, examining symmetries, Planck's constant, and prequantization to determine quantum states through inequalities.
Explore geometric formulation of quantum states using Lagrangian polar duality, challenging traditional uncertainty principle interpretations and quantum mechanics concepts.
Explore the unification of Cencov's and Petz's theorems through W*-algebra formulations of classical and quantum information geometry.
Explore scalar curvature monotonicity in quantum exponential family for transverse-field Ising chains, examining finite-size effects and implications for Petz conjecture.
Explore statistical methods for medical image processing and reconstruction, from basic to advanced Bayesian approaches, across various imaging modalities.
Explore transverse Poisson structures in complex semi-simple Lie algebras, focusing on adjoint orbits and their nilpotent cases. Discover determinantal formulas and quasihomogeneous polynomials in this advanced mathematical topic.
Explore entropy estimation in data science using kernel methods and quantum information theory for covariance matrices.
Explore the intersection of hydrodynamics, computation, and contact geometry. Discover how fluid dynamics can simulate universal Turing machines and its implications for undecidable fluid paths and celestial mechanics.
Explore the Variational Gaussian approximation technique for optimizing the Kushner filter, enhancing signal processing and estimation capabilities.
Explore f-divergences between hyperboloid models in this concise conference talk, delving into mathematical concepts and their applications in geometric analysis.
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