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Full Description
The Inaugural International Workshop on Applied Mathematics and Machine Learning aspires to convene a distinguished assembly of scientists, scholars, and innovators dedicated to advancing the frontiers of mathematical inquiry and its transformative applications across diverse scientific realms. This prestigious gathering seeks to illuminate the latest developments in mathematical modeling, computational techniques, and their synergistic interplay with machine learning, fostering a vibrant exchange of ideas that bridges theoretical rigor with practical impact.
The workshop will delve into a constellation of pivotal themes, including Inverse Problems, Partial Differential Equations, Mathematical Control, Numerical Analysis, and Computer Science. A particular emphasis will be placed on the burgeoning domain of inverse problems, whose integration with computer science remains a fertile yet underexplored frontier. Despite its rapid evolution, this field has yet to be fully anchored by robust mathematical frameworks—a gap this event is poised to address through rigorous exploration and insightful discourse.
Our ambition is to deliver profound mathematical insights paired with expressive, accurate applications that resonate across disciplines. By spotlighting emerging trends and fostering interdisciplinary collaboration, the workshop aims to catalyze innovative solutions that harness the power of mathematics to tackle complex challenges in science and industry. The growing prominence of these topics in both academic discourse and industrial innovation ensures that this event will captivate a diverse audience, from mathematicians and computer scientists to engineers and industry leaders.
Contents
Boundary Reconstruction for the 2D Telegraph Equation using a Relaxed Iterative Algorithm.- Copula-Based Single X-Ray Poisson Image Demixing.- Fractional-Order PDE Systems for Enhanced Image Noise Reduction.- Solving Ill-Posed Problems at Tassemit Site: A Regularized Framework for Cost and Cn2(z) Reconstruction.- Lagrange-Chebyshev Interpolation for Single Image Super-Resolution: A Non-Standard Approach.- Beyond Classical Diffusion: Tensor-Guided PDEs with Primal-Dual Optimization for Superior Image Denoising.- Adaptive Norm Selection for Banach Wasserstein Generative Adversarial Networks.- An Inverse Boundary Value Problem with Integral Constraints: BEM Approach and Error Analysis.- Existence Theory via Leray-Schauder Degree: Applications to Ill-Posed and Nonlinear PDE Problems.- Numerical Study of an Inverse Space-Dependent Force Problems for the Wave Equation.- An Improved Stochastic Accelerated Fixed-Point Iteration Approach for Image Super-Resolution.- Modeling Infectious Disease Spread with Vector-Environment Interactions.- Time Fractional p(x)-Laplacian Diffusion for Adaptive Image Denoising.- Efficient Convolutional Denoising via Deep Residual Stacking.- Fredholm Formulation and Haar-Wavelet Regularization for a Cauchy Problem.- Stabilization of the Elliptic Cauchy Problem : An Optimal Control and Tikhonov regularization approach.- Decoding the Hidden Heartbeat: Copula-Based Fetal ECG Extraction.
