Softcover ISBN: 978-1-4704-7634-2
Product Code: CONM/820
Contemporary Mathematics Volume: 820;
2025; 225 pp
MSC: Primary 32; 30; 37; 33; 51
This volume contains the proceedings of the 29th International Conference on Finite or Infinite Dimensional Complex Analysis and Applications, held August 21?25, 2023, at Pondicherry University, Puducherry, India.
It covers a wide range of papers on complex analysis and provides a broad survey of the present state of research in various aspects of geometric function theory.
The papers in this volume reflect the directions of research in different areas of finite- and infinite-dimensional complex analysis and also give the reader an idea of how these branches of complex analysis intersect with other areas of mathematics. They will be suitable for specialists as well as aspiring researchers who are interested in various areas of geometric function theory.
Graduate students and research mathematicians interested in complex analysis and geometric function theory.
Kuntal Banerjee and Anubrato Bhattacharyya ? Paths of analytic circle diffeomorphisms
Prachi Prajna Dash and Jugal Kishore Prajapat ? Certain subclass of harmonic functions associated with univalent functions
Xinlong Dong ? Some geometrical applications of tame quasiconformal motions
Krishnendu Gongopadhyay and Abhishek Mukherjee ? On compositions of quaternionic Mobius transformations
Yunping Jiang ? Tameness conditions in complex dynamics and in quasiconformal motions
Nishan Chatterjee, Arshiya Farhath. G and Sudeb Mitra ? Holomorphic motions and related topics ? A brief survey
Rakesh K. Parmar and Uthara S ? On generalized extended Voigt-type function and associated bounds
Rakesh K. Parmar, Tibor K. Pogany and Agnihotri Roy ? Generalized multiple Mordell?Tornheim zeta function, related integral forms, bounds and inequalities
Dragana Jankov Ma?irevi? and Tibor K. Pogany ? On distribution of Rice?Middleton model II. Srivastava?Daoust
function approach
Marrikanti Keerthana Reddy, Saminathan Ponnusamy and Karl-Joachim Wirths ? Modified Bohr phenomena for some classes of functions
Ritwick Maity and Swadesh Kumar Sahoo ? Geometry of stereographic (type) projections I
Yao Liang Chung, Maisarah Haji Mohd and See Keong Lee ? Some results on a subclass of analytic univalent functions
Armen Sergeev ? Mathematical approach to the theory of topological insulators
Ryan Gibara and Nageswari Shanmugalingam ? On the Dirichlet-to-Neumann map for the
-Laplacian on a metric measure space
O. S. Kudryavtseva and A. P. Solodov ? Becker?Pommerenke type inequalities and domains of univalence
Toshiyuki Sugawa ? Quasiconformal distortion of hyperbolic distances
Vesna Todor?evi? ? Harmonic quasiconformal mappings, Ahlfors regular and Bishop-Jones domains
Molla Basir Ahamed and Vasudevarao Allu ? Dynamical behavior of meromorphic solutions for certain complex difference equations
Softcover ISBN: 978-1-4704-7586-4
Product Code: CONM/821
Expected availability date: August 09, 2025
Contemporary Mathematics Volume: 821;
2025; 179 pp
MSC: Primary 14; 53
This volume contains the proceedings of the AMS Special Session on Recent Advanced in Differential Geometry, held virtually on April 1?2, 2023, and the Tenth Congress of Romanian Mathematicians Special Session on Recent Advances in the Geometry of Submanifolds, held on June 30?July 5, 2023, in Pite?ti, Romania.
In the last two decades, various techniques produced new results in differential geometry and many of them focused on the geometry of submanifolds, where one of the most important questions, the Willmore conjecture, was solved in 2012 by A. Neves and F. Coda Marques. This invites a reflection on the new trends and research directions that contemporary differential geometry might and will take in its natural development. Some of the most important advances have been obtained by using techniques in geometric analysis, while others have been using more classical methods, which are still of interest.
Motivated by these new developments, the present volume intends to bring together various viewpoints on the recent study of representing the fundamental idea of space in differential geometry. Of particular interest are the results focused on minimal submanifolds and their generalizations and the related concept of harmonic mappings and their generalizations. In preparing this volume, the editors were particularly interested in the study of curvature functionals in various contexts, from comparison geometry to new curvature invariants, relations between curvature and topology, as well as other related topics.
Graduate students and research mathematicians interested in differential geometry.
Rare? Ambrosie ? Harmonicity and biharmonicity of quadratic maps between spheres
Mateo Anarella ? A survey on submanifolds of nearly Kahler spaces
Yusei Aoki and Toshiaki Adachi ? Expressions of circles in a complex hyperbolic space by trajectories on tubes around complex hyperplanes
Volker Branding ? On conservation laws for polyharmonic maps
Simona Decu and Gabriel-Eduard Vilcu ? Chen inequality for statistical submanifolds in Kenmotsu statistical manifolds of constant
-sectional curvature
Marie Dfhaene ? Thurston geometries in dimension four from a Riemannian perspective
Amalendu Ghosh, Ramesh Sharma and Rahul Poddar ? Recent results in Ricci and Yamabe solitons in contact geometry
Hsiao-Fan Liu ? Understanding of constant
-mean curvature hypersurfaces in the Heisenberg groups
Rafael Lopez ? Open problems on compact constant mean curvature surfaces with boundary
Andreas Malmendier and Michael T. Schultz ? On holomorphic conformal structures associated with lattice polarized K3 surfaces
S. Montaldo and A. Ratto ? Triharmonic curves in the
-dimensional Sol space
Ana Irina Nistor ? A note on Weingarten surfaces foliated by helices
Alvaro Pampano ? Characterizations of rotational biconservative hypersurfaces
Alexander Pigazzini, Luca Lussardi, Magdalena Toda and Andrew DeBenedictis ? Einstein warped-product manifolds and the screened Poisson equation
Softcover ISBN: 978-1-4704-7496-6
Product Code: CONM/822
Contemporary Mathematics Volume: 822;
2025; 210 pp
MSC: Primary 33; 42; 65
This volume contains the proceedings of the AMS Special Session on Orthogonal Polynomials and their Applications, held January 4?7, 2023, in Boston as part of the Joint Mathematics Meetings.
Orthogonal polynomials are classical objects with important connections to many areas of mathematics, such as approximation theory, integrable systems, and mathematical physics. This volume reflects the wide variety of topics of current interest in the orthogonal polynomial community. Specific topics appearing in this volume include exceptional orthogonal polynomials, non-Hermitian orthogonal polynomials, multiple orthogonal polynomials, and applications to numerical linear algebra and integrable probability.
Graduate students and research mathematicians interested in special functions and orthogonal polynomials.
Cade Ballew and Thomas Trogdon ? The Akhiezer iteration
Ahmad Barhoumi, Pavel Bleher, Alfredo Deano and Maxim Yattselev ? On Airy solutions of P
and the complex cubic ensemble of random matrices, II
U. Fidalgo ? Multi-orthogonal polynomials associated to a bulk queueing model
Roozbeh Gharakhloo and Karl Liechty ? Bordered and framed Toeplitz and Hankel determinants with applications in integrable probability
Alex Kasman and Robert Milson ? Two useful facts about generating functions
Luke Paluso and Alex Kasman ? Exceptional Hermite polynomials and Calogero-Moser pairs
Steven H. Weintraub ? Reverse orthogonal polynomials
Tewodros Amdeberhan and Victor H. Moll ? The integrality of reverse Legendre polynomials
Maxim L. Yattselev ? On an identity by Ercolani, Lega, and Tippings
Hardback ISBN: 9780443417894
Machine Learning Solutions for Inverse Problems: Part A, Volume 26 in the Handbook of Numerical Analysis, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Data-Driven Approaches for Generalized Lasso Problems, Implicit Regularization of the Deep Inverse Prior via (Inertial) Gradient Flow, Generalized Hardness of Approximation, Hallucinations, and Trustworthiness in Machine Learning for Inverse Problems, Energy-Based Models for Inverse Imaging Problems, Regularization Theory of Stochastic Iterative Methods for Solving Inverse Problems, and more.
Other sections cover Advances in Identifying Differential Equations from Noisy Data Observations, The Complete Electrode Model for Electrical Impedance Tomography: A Comparative Study of Deep Learning and Analytical Methods, Learned Iterative Schemes: Neural Network Architectures for Operator Learning, Jacobian-Free Backpropagation for Unfolded Schemes with Convergence Guarantees, and Operator Learning Meets Inverse Problems: A Probabilistic Perspective
1. Data-Driven Approaches for Generalized Lasso Problems
2. Implicit Regularization of the Deep Inverse Prior via (Inertial) Gradient Flow
3. Generalized Hardness of Approximation, Hallucinations, and Trustworthiness in Machine Learning for Inverse Problems
4. Energy-Based Models for Inverse Imaging Problems
5. Regularization Theory of Stochastic Iterative Methods for Solving Inverse Problems
6. Advances in Identifying Differential Equations from Noisy Data Observations
7. The Complete Electrode Model for Electrical Impedance Tomography: A Comparative Study of Deep Learning and Analytical Methods
8. Learned Iterative Schemes: Neural Network Architectures for Operator Learning
9. Jacobian-Free Backpropagation for Unfolded Schemes with Convergence Guarantees
10. Operator Learning Meets Inverse Problems: A Probabilistic Perspective
Series: Institute of Mathematical Statistics Monographs
Published: March 2025
Format: Hardback
ISBN: 9781009584111
Bringing together years of research into one useful resource, this text empowers the reader to creatively construct their own dependence models. Intended for senior undergraduate and postgraduate students, it takes a step-by-step look at the construction of specific dependence models, including exchangeable, Markov, moving average and, in general, spatio-temporal models. All constructions maintain a desired property of pre-specifying the marginal distribution and keeping it invariant. They do not separate the dependence from the marginals and the mechanisms followed to induce dependence are so general that they can be applied to a very large class of parametric distributions. All the constructions are based on appropriate definitions of three building blocks: prior distribution, likelihood function and posterior distribution, in a Bayesian analysis context. All results are illustrated with examples and graphical representations. Applications with data and code are interspersed throughout the book, covering fields including insurance and epidemiology.
Provides the reader with powerful tools for constructing any dependence model with invariant distribution
Illustrates the use of the models with real data and provides BUGS code for implementing them
Shows the construction of different kinds of dependencies from exchangeable, Markov, moving average and spatio-temporal
1. Introduction
2. Conjugate models
3. Exchangeable sequences
4. Markov sequences
5. General dependent sequences
6. Temporal dependent sequences
7. Spatial dependent sequences
8. Multivariate dependent sequences
Appendix. Data sets
References
Index.
Published: May 2025
Format: Hardback
ISBN: 9781009397612
James Clerk Maxwell is one of the giants of scientific thought, and whilst his groundbreaking contributions to electromagnetism and statistical physics are well known, his profound insights into the theory of structures are appreciated less widely. Maxwell's approach was deeply geometrical, and this richly illustrated book reveals his astute perception of the remarkable dualities that exist between the form of a structure and the forces it can carry, with understandings that will surprise contemporary readers. Early chapters introduce the background in which Maxwell was working, followed by contributions by leading researchers describing the latest applications of these ideas. Subsequent chapters introduce the many subtopics that this work embraces. The book ends with Maxwell's original papers on structural mechanics, each annotated to highlight and explain the ideas therein. This is a wonderful resource for mathematicians, scientists, engineers, and designers to enter this rich and underexplored aspect of the genius of Maxwell.
Shines a light on Maxwell's previously overlooked work in structural mechanics
Renders Maxwell's work accessible to the modern reader, combining annotations of the original texts with detailed summaries
Includes rediscovered ideas, with exciting applications in the 21st century
James Clerk Maxwell is one of the giants of scientific thought, and whilst his groundbreaking contributions to electromagnetism and statistical physics are well known, his profound insights into the theory of structures are appreciated less widely. Maxwell's approach was deeply geometrical, and this richly illustrated book reveals his astute perception of the remarkable dualities that exist between the form of a structure and the forces it can carry, with understandings that will surprise contemporary readers. Early chapters introduce the background in which Maxwell was working, followed by contributions by leading researchers describing the latest applications of these ideas. Subsequent chapters introduce the many subtopics that this work embraces. The book ends with Maxwell's original papers on structural mechanics, each annotated to highlight and explain the ideas therein. This is a wonderful resource for mathematicians, scientists, engineers, and designers to enter this rich and underexplored aspect of the genius of Maxwell.
List of Contributors
Preface
Editorial note
Part I. Maxwell and Structural Mechanics:
1. James Clerk Maxwell and structural mechanics William Baker and John Ochsendorf
2. The importance of Maxwell's writings for 21st-century structural mechanics William Baker, Petia Tzokova, Juney Lee and Allan McRobie
3. Geometric rigidity theory Robert Connelly, Simon Guest, Bernd Schulze and Walter Whiteley
4. Maxwell's relevance to modern research in materials Heinrich Jaeger, Sidney Nagel and Vincenzo Vitelli
5. Isotropic and architectural geometry Cameron Millar and Helmut Pottmann
6. A brief introduction to mid-19th-century projective geometry and topology Marina Konstantatou and William Baker
Part II. Concepts from Maxwell's Articles on Structural Mechanics:
Published: June 2025
Format: Hardback
ISBN: 9781009449434
Covering formulation, algorithms and structural results and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of partially observed Markov decision processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students and researchers in engineering, operations research, and economics to understand the underlying unifying themes without getting weighed down by mathematical technicalities. In light of major advances in machine learning over the past decade, this edition includes a new Part V on inverse reinforcement learning as well as a new chapter on non-parametric Bayesian inference (for Dirichlet processes and Gaussian processes), variational Bayes and conformal prediction.
Links theory to real-world applications in controlled sensing
Consolidates results from across the literature of multiple different disciplines into a centralized resource
Presents the key ideas underpinning Bayesian filtering, POMDPs, reinforcement learning, and inverse reinforcement learning in an accessible way
Preface to revised edition
Notation
1. Introduction
I. Stochastic Models and Bayesian Filtering:
2. Stochastic state space model
3. Optimal filtering
4. Algorithms for maximum likelihood parameter estimation
5. Multi-agent sensing: social learning and data incest
6. Nonparametric Bayesian inference
II. POMDPs: Models and Applications:
7. Fully observed Markov decision processes