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We introduce a new framework for learning dense correspondence between deformable 3D shapes. Existing learning based approaches model shape correspondence as a labelling problem, where each point of a query shape receives a label…

Computer Vision and Pattern Recognition · Computer Science 2017-08-01 Or Litany , Tal Remez , Emanuele Rodolà , Alex M. Bronstein , Michael M. Bronstein

Conformal geometry is studied using the unfolded formulation \`a la Vasiliev. Analyzing the first-order consistency of the unfolded equations, we identify the content of zero-forms as the spin-two off-shell Fradkin-Tseytlin module of…

High Energy Physics - Theory · Physics 2022-01-05 Euihun Joung , Min-gi Kim , Yujin Kim

This paper describes an algorithm for the compilation of a two (or more) level orthographic or phonological rule notation into finite state transducers. The notation is an alternative to the standard one deriving from Koskenniemi's work: it…

cmp-lg · Computer Science 2008-02-03 Edmund Grimley-Evans , George Anton Kiraz , Stephen G. Pulman

In the study of 2d (the space dimension) topological orders, it is well-known that bulk excitations are classified by unitary modular tensor categories. But these categories only describe the local observables on an open 2-disk in the long…

Quantum Algebra · Mathematics 2018-06-18 Yinghua Ai , Liang Kong , Hao Zheng

We consider a multiscale approach based on immersed methods for the efficient computational modeling of tissues composed of an elastic matrix (in two or three-dimensions) and a thin vascular structure (treated as a co-dimension two…

Numerical Analysis · Mathematics 2021-11-18 Luca Heltai , Alfonso Caiazzo

This paper introduces a general method for the exploration of equivalence classes in the input space of Transformer models. The proposed approach is based on sound mathematical theory which describes the internal layers of a Transformer…

Machine Learning · Computer Science 2025-10-23 Alessandro Benfenati , Alfio Ferrara , Alessio Marta , Davide Riva , Elisabetta Rocchetti

We construct the quasi-classical approximation of the form factors in finite volume using the separation of variables. The latter is closely related to the Baxter equation.

High Energy Physics - Theory · Physics 2007-05-23 Feodor A. Smirnov

The recent proliferation of richly structured probabilistic models raises the question of how to automatically determine an appropriate model for a dataset. We investigate this question for a space of matrix decomposition models which can…

Machine Learning · Computer Science 2012-10-19 Roger Grosse , Ruslan R Salakhutdinov , William T. Freeman , Joshua B. Tenenbaum

We develop a framework for extracting a concise representation of the shape information available from diffuse shading in a small image patch. This produces a mid-level scene descriptor, comprised of local shape distributions that are…

Computer Vision and Pattern Recognition · Computer Science 2015-04-15 Ying Xiong , Ayan Chakrabarti , Ronen Basri , Steven J. Gortler , David W. Jacobs , Todd Zickler

Weighted Triebel-Lizorkin and Besov spaces on the unit ball $B^d$ in $\Rd$ with weights $\W(x)= (1-|x|^2)^{\mu-1/2}$, $\mu \ge 0$, are introduced and explored. A decomposition scheme is developed in terms of almost exponentially localized…

Classical Analysis and ODEs · Mathematics 2007-05-23 G. Kyriazis , P. Petrushev , Yuan Xu

Dissipative dynamical systems characterised by two basins of attraction are found in many physical systems, notably in hydrodynamics where laminar and turbulent regimes can coexist. The state space of such systems is structured around a…

Fluid Dynamics · Physics 2020-09-11 Miguel Beneitez , Yohann Duguet , Philipp Schlatter , Dan S. Henningson

Many systems in biology, physics and engineering can be described by systems of ordinary differential equation containing many parameters. When studying the dynamic behavior of these large, nonlinear systems, it is useful to identify and…

Molecular Networks · Quantitative Biology 2016-04-13 Heather A. Harrington , Dhagash Mehta , Helen M. Byrne , Jonathan D. Hauenstein

Word embeddings are rich word representations, which in combination with deep neural networks, lead to large performance gains for many NLP tasks. However, word embeddings are represented by dense, real-valued vectors and they are therefore…

Computation and Language · Computer Science 2019-12-24 Andreas Hanselowski , Iryna Gurevych

We address the problem of analytically extracting a countable infinity of flat, non-dispersive bands in a periodic array of cells that comprise branching Vicsek geometries of higher and higher generations. Through a geometric construction,…

Mesoscale and Nanoscale Physics · Physics 2022-11-15 Sougata Biswas , Amrita Mukherjee , Arunava Chakrabarti

We investigate the self-organization of strongly interacting particles confined in 1D and 2D. We consider hardcore bosons in spinless Hubbard lattice models with short-range interactions. We show that many-body states with topological…

Strongly Correlated Electrons · Physics 2019-09-12 Ioannis Kleftogiannis , Ilias Amanatidis

The study of random landscapes has long relied on counting stationary points: metastable states and the barriers between them. However, this method is useless for describing flat regions, common in constraint satisfaction problems. We…

Disordered Systems and Neural Networks · Physics 2026-02-16 Jaron Kent-Dobias

We show that band topology can dramatically change the photophysics of two-dimensional (2D) semiconductors. For systems in which states near the band extrema are of multiple orbitals character and the spinors describing the orbital…

Mesoscale and Nanoscale Physics · Physics 2018-02-28 Ting Cao , Meng Wu , Steven G. Louie

We provide a two dimensional deformation model to describe how soft squishy circular particles respond to external forces and collisions. This model involves formulating mathematical equations and algorithms for the shape of a deformed…

Soft Condensed Matter · Physics 2024-08-28 Roshan Maharana

In these notes we give a brief introduction to decomposition theory and we summarize some classical and well-known results. The main question is that if a partitioning of a topological space (in other words a decomposition) is given, then…

Geometric Topology · Mathematics 2021-03-05 Boldizsar Kalmar

Partitionings (or segmentations) divide a given domain into disjoint connected regions whose union forms again the entire domain. Multi-dimensional partitionings occur, for example, when analyzing parameter spaces of simulation models,…

Human-Computer Interaction · Computer Science 2024-10-28 Marina Evers , Lars Linsen