The Seventh ARTA (""Advances in Representation Theory of Algebras VII"") conference took place at the Instituto de Matemáticas of the Universidad Nacional Autónoma de México, in Mexico City, from September 24-28, 2018, in honor of José Antonio de la Peña's 60th birthday.Papers in this volume cover topics Professor de la Peña worked on, such as covering theory, tame algebras, and the use of quadratic forms in representation theory. Also included are papers on the categorical approach to representations of algebras and relations to Lie theory, Cohen-Macaulay modules, quantum groups and other alg.
Representation is integral to the functioning and legitimacy of modern government. Yet political theorists have often been reluctant to engage directly with questions of representation, and empirical political scientists have closed down such questions by making representation synonymous with congruence. Conceptually unproblematic and normatively inert for some, representation has been deemed impossible to pin down analytically and to defend normatively by others. But this is changing. Political theorists are now turning to political representation as a subject worthy of theoretical investigation in its own right. In their effort to rework the theory of political representation, they are also hoping to impact how representation is assessed and studied empirically. This volume gathers together chapters by key contributors to what amounts to a "representative turn" in political theory. Their approaches and emphases are diverse, but taken together they represent a compelling and original attempt at re-conceptualizing political representation and critically assessing the main theoretical and political implications following from this, namely for how we conceive and assess representative democracy. Each contributor is invited to look back and ahead on the transformations to democratic self-government introduced by the theory and practice of political representation. Representation and democracy: outright conflict, uneasy cohabitation, or reciprocal constitutiveness? For those who think democracy would be better without representation, this volume is a must-read: it will question their assumptions, while also exploring some of the reasons for their discomfort. Reclaiming Representation is essential reading for scholars and graduate researchers committed to staying on top of new developments in the field.
This volume presents a collection of articles devoted to representations of algebras and related topics. Dististinguished experts in this field presented their work at the International Conference on Representations of Algebras, which took place in Bielefeld in 2012. Many of the expository surveys are included here. Researchers of representation theory will find in this volume interesting and stimulating contributions to the development of the subject.
This volume presents a collection of articles devoted to representations of algebras and related topics. Dististinguished experts in this field presented their work at the International Conference on Representations of Algebras which took place 2012 in Bielefeld. Many of the expository surveys are included here. Researchers of representation theory will find in this volume interesting and stimulating contributions to the development of the subject.
The Seventh ARTA (“Advances in Representation Theory of Algebras VII”) conference took place at the Instituto de Matemáticas of the Universidad Nacional Autónoma de México, in Mexico City, from September 24–28, 2018, in honor of José Antonio de la Peña's 60th birthday. Papers in this volume cover topics Professor de la Peña worked on, such as covering theory, tame algebras, and the use of quadratic forms in representation theory. Also included are papers on the categorical approach to representations of algebras and relations to Lie theory, Cohen–Macaulay modules, quantum groups and other algebraic structures.
In 1991-1993 our three-volume book "Representation of Lie Groups and Spe cial Functions" was published. When we started to write that book (in 1983), editors of "Kluwer Academic Publishers" expressed their wish for the book to be of encyclopaedic type on the subject. Interrelations between representations of Lie groups and special functions are very wide. This width can be explained by existence of different types of Lie groups and by richness of the theory of their rep resentations. This is why the book, mentioned above, spread to three big volumes. Influence of representations of Lie groups and Lie algebras upon the theory of special functions is lasting. This theory is developing further and methods of the representation theory are of great importance in this development. When the book "Representation of Lie Groups and Special Functions" ,vol. 1-3, was under preparation, new directions of the theory of special functions, connected with group representations, appeared. New important results were discovered in the traditional directions. This impelled us to write a continuation of our three-volume book on relationship between representations and special functions. The result of our further work is the present book. The three-volume book, published before, was devoted mainly to studying classical special functions and orthogonal polynomials by means of matrix elements, Clebsch-Gordan and Racah coefficients of group representations and to generaliza tions of classical special functions that were dictated by matrix elements of repre sentations.
This volume consists of contributions invited articles from the MPI-summer program on representation theory in 2007. There will be an even mix of high quality overview articles and original research contributions. The targeted audience is graduate students and researchers in representation theory, harmonic analysis, automorphic forms, number theory, and locally symmetric spaces.
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
