Results 81 to 90 of about 1,030 (160)
Mathematical Finance, EarlyView.ABSTRACT We study a dynamic portfolio optimization problem under the mean–variance–variance (M‐V‐V) criterion proposed by Maccheroni et al. It is an analogue of the Arrow–Pratt approximation to the well‐known smooth ambiguity model. Under the standard Black–Scholes framework, we derive fully explicit equilibrium investment strategies in which a DM's ...
David Landriault, Bin Li, Yuanyuan Zhang
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Generalized J-integral – mathematical foundation
Boundary Value ProblemsThis article describes the mathematics for building the foundations of the theory of the Generalized J-integral (GJ-integral) in various variational problems defined on D that gives the shape derivative on singular points such as boundaries, cracks ...
Kohji Ohtsuka
doaj +1 more source
Fréchet-Derivative-Based Global Sensitivity Analysis and Its Physical Meanings in Structural Design
Applied SciencesSensitivity analysis is essential for uncertainty-based structural design and analysis, especially global sensitivity analysis, which can reflect the overall physical properties of large and complex computational models with stochastic parameters.
Weifeng Tao, Zhiqiang Wan, Xiuli Wang
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Information‐Theoretic Approach to Financial Market Modeling
Mathematical Finance, EarlyView.ABSTRACT The paper treats the financial market as a communication system, using four information‐theoretic assumptions to derive an idealized model with only one parameter. State variables are scalar stationary diffusions. The model maximizes the surprisal of the market and minimizes the Kullback–Leibler divergence between the benchmark‐neutral pricing
Eckhard Platen
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Risk Measure Duality Without Structure
Mathematical Finance, EarlyView.ABSTRACT We study risk measures on vector spaces of random variables which a priori have little structure, such as spaces lacking law invariance or a lattice structure. Ensuring the existence of a tractable dual representation (one which does not contain non‐sigma‐additive measures) is one of the main problems in risk measure theory, and we address it ...
Vasily Melnikov
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Animal Genetics, Volume 57, Issue 6, December 2026.ABSTRACT Generative adversarial networks (GANs) are artificial intelligence models designed to generate novel data that is indistinguishable from real data. Originally developed to generate images to complement existing datasets and create more diverse samples, GAN‐based data can enhance downstream analysis for machine learning and deep learning ...
Edgar Caballero Vargas, Tiago Bresolin
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Computational and Systems Oncology, Volume 6, Issue 1, December 2026.ABSTRACT Rare cancers collectively represent 20%–25% of all malignancies yet yield fewer than 50 annotated whole‐slide images (WSIs) per subtype in publicly available archives, rendering supervised deep learning inapplicable. We present HierAnom‐Path, to the best of our knowledge, the first framework for zero‐shot rare cancer anomaly detection in ...
Noora Saleem Jumaah +5 more
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Gradient Flows on Sparse Representations for PDE‐Regularized Inverse Problems
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.ABSTRACT In this short paper, we summarize the theory of Atomic Gradient Flows (AGF) introduced in (Amend, Carioni and Zemas, arxiv:2603.25675, 2026), which provides a framework to construct gradient flows on sparse representations for convex regularized optimization problems.
Christian Amend, Marcello Carioni
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Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.ABSTRACT We consider optimal control of the heat equation where the control variable appears linearly as a boundary control. We establish switching times optimization for bang–bang controls with multiple switching times. Particularly, representations of variational derivatives of the state and the cost w.r.t. switching times are given.
Georg Vossen
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Inverse problems for semilinear elliptic PDE with a general nonlinearity a(x,u)$a(x,u)$
Transactions of the London Mathematical Society, Volume 13, Issue 1, December 2026.Abstract This article studies the inverse problem of recovering a nonlinearity in an elliptic equation Δu+a(x,u)=0$\Delta u + a(x,u) = 0$ from boundary measurements of solutions. Previous results based on first‐order linearization achieve this under a sign condition on ∂ua(x,u)$\partial _u a(x,u)$, and results based on higher order linearization ...
David Johansson +2 more
wiley +1 more source