Study classifies equidistant decompositions in 2D spaces.
problem Classifying equidistant decompositions in 2D spaces.
method Full classification of decompositions in Euclidean plane and sphere.
result Complete classification of equidistant decompositions in 2D spaces.
Maps between 2D spaces evolve under area-decreasing conditions.
problem Understanding the evolution of maps under area-decreasing constraints.
method Mean curvature flow of the graph of a map between 2D Euclidean spaces.
result Existence and uniform decay estimates for the evolving submanifold.
Sharp isoperimetric inequality for minimal submanifolds in 2D and higher Euclidean space.
problem Finding the minimum surface area for a given volume in submanifolds.
method Proving a Sobolev inequality and using it to derive a sharp isoperimetric inequality.
result Sharp isoperimetric inequality for minimal submanifolds in Euclidean space of codimension at most 2.
The paper classifies 2D complete λ-surfaces in 3D space.
problem Classifying complete λ-surfaces in R3. method Complete classification of 2D complete λ-surfaces with constant squared norm of the second fundamental form. result A complete classification for 2-dimensional complete λ-surfaces in Euclidean space R3 with constant squared norm of the second fundamental form. Study of curve evolution in 2D space forms converging to a circle.
problem Understanding curve evolution in 2D space forms.
method Inverse curvature flow with normal speed defined by weighted inverse curvature and support function.
result Solutions exist for all time and converge exponentially to a standard round geodesic circle.
Paper proves rigidity of certain 2D Lagrangian shapes in 4D space.
problem Proving rigidity of specific Lagrangian shapes in 4D space.
method Used a rigidity theorem for 2D complete Lagrangian self-shrinkers.
result Rigidity of 2D complete Lagrangian self-shrinkers with constant squared norm of mean curvature vector.
Random complexes can be embedded linearly if certain conditions on parameters are met.
problem Embedding random simplicial complexes linearly in Euclidean space.
method Established strict inequalities on parameters for linear embedding into R^(2d).
result Necessary and sufficient conditions for linear embedding of random complexes.
Study of harmonic maps on 2D simplicial complexes, proving existence and regularity.
problem Existence and regularity of harmonic maps between 2D simplicial complexes.
method Extending previous work, study metrics conformal to flat or ideal hyperbolic, proving existence, uniqueness, and regularity of harmonic maps.
result Existence, uniqueness, and regularity results for harmonic maps between 2D simplicial complexes.
We prove that the associativity equations of two-dimensional topological quantum field theories are very natural reductions of the fundamental nonlinear equations of the theory of submanifolds in pseudo-Euclidean spaces and give a natural class of potential flat torsionless submanifolds. We show that all potential flat…
In this paper, we study the bound states of quantum layers. We prove that for the quantum layer built over a parabolic manifold which is not totally geodesic, if the second fundamantal form decays sufficiently fast, then the bound states exist. In the 2d case, we prove that the quantum layer over a convex surface whose…
Study the periods mapping from hyperelliptic curves, revealing fiber topology.
problem Global topology of 2D fibers of the periods mapping.
method Decomposition of moduli space into polyhedra labeled by planar graphs.
result Investigation of low dimensional fibers of the periods mapping.
Researchers study Killing superalgebras in 2D manifolds.
problem Characterizing Killing superalgebras in 2D pseudo-Riemannian manifolds.
method Computing Spencer cohomology and filtered deformations of superalgebras.
result Killing superalgebras arise as solutions for geometric and skew-Killing spinors.
Study optimizes submatrices in 2D spaces, linking to polygon geometry.
problem Optimizing submatrices in 2-dimensional linear subspaces. method Optimization problem for isoperimetric polygons in Euclidean spaces.
result New geometrical perspective on a linear subspace problem.
The objective of this paper is to present some geometric aspects of surfaces associated with theta function solutions of the periodic 2D-Toda lattice. For this purpose we identify the (N2−1)-dimensional Euclidean space with the su(N) algebra which allows us to construct the generalized Weierstrass formula …
New method reconstructs 3D shapes from 2D images using Kendall's shape space.
problem Reconstruct 3D shapes from 2D images, especially for rare specimens.
method Kendall's shape space approach with prior information.
result More robust and plausible shapes compared to previous methods.
Curvature of 2D subsets preserved in their space.
problem Understanding curvature of subsets in 2D spaces.
method Analyzing subsets with vanishing first homology.
result Closed subsets inherit curvature bounds from ambient spaces.
A neural flow method minimizes Willmore energy for 2-surfaces in 3D space.
problem Minimizing Willmore energy for closed oriented 2-surfaces in 3D space.
method Introducing neural Willmore flow to model and minimize the Willmore energy using neural architectures.
result The neural flow reproduces expected round sphere and Clifford torus for genus 0 and 1 surfaces, respectively, and finds minimal Willmore surfaces for genus 2.
Algorithms compute the topology of hyperelliptic curves in 2D and 3D.
problem Computing the topology of hyperelliptic curves in higher dimensions.
method Birational mapping of the plane or space to compute the topology of the curve.
result Algorithms implemented in { t Maple} for computing the topology of hyperelliptic curves.
Constructs minimal surfaces in 4D space from 2D graphs.
problem Minimal surfaces in Euclidean 4-space.
method Generalizing Cauchy-Riemann equations to construct Osserman system.
result Minimal surfaces in 4D space have a complex projective intersection.
Sharp area bounds for 2D free boundary minimal surfaces in a sphere.
problem Sharp bounds for the area of minimal surfaces in a geodesic ball of the sphere.
method Extending earlier work by Brendle and Fraser-Schoen, applying to higher dimensions.
result New sharp bounds for area of free boundary minimal surfaces in higher dimensions.
Study Ricci vector fields on 2D space with diagonal metrics.
problem Understanding Ricci vector fields on 2D space with specific metrics.
method Examined Ricci vector fields on R2 with a diagonal metric. result Characterized Ricci vector fields on R2 with a diagonal metric. New model preserves symmetry in multivariate time series, improving performance.
problem Implicit ordering in MTS models violates inherent exchangeability.
method Permutation-equivariant 2D state space model with canonical architecture.
result Eliminates sequential dependency chains and simplifies stability analysis.
This paper analyzes shallow ReLU networks in L^p and Sobolev spaces, focusing on approximation and generalization.
problem Approximation and generalization of shallow ReLU networks in L^p and Sobolev spaces.
method Spherical harmonic analysis and embeddings into spectral Barron spaces for L^p spaces, path-norm control for Sobolev spaces.
result Minimax-optimal rates for nonparametric regression with shallow ReLU networks under path-norm control.
Proposes a model to generate 3D-aware images from 2D images.
problem Generating 3D-aware images from 2D images.
method Likelihood-based top-down model using Neural Radiance Fields and energy-based latent variables.
result Model can infer 3D object structures from 2D images and generate novel views.
The paper lists all self-similar solutions for a flow in 2D space.
problem Finding solutions to the inverse mean curvature flow in 2D.
method Obtained a complete list of self-similar solutions.
result Completely enumerated all self-similar solutions for the flow.
Study 2D spaces with curvature, finding a graph structure.
problem Understanding the geometry of 2D spaces with curvature constraints.
method Analyzing spaces as unions of disks, identifying singular points.
result Obtained a graph structure of topological singular points.
Optimizes master faces for 2D and 3D face verification using evolutionary algorithms and neural networks.
problem Impersonation attacks using master faces for face-based identity authentication.
method Evolutionary algorithm in latent space of StyleGAN, neural network to direct search, 2D and 3D face reconstruction.
result Obtains high impersonation rates with fewer master faces for 2D and 3D face verification.
The investigation of 3D euclidean symmetry sets (SS) and medial axis is an important area, due in particular to their various important applications. The pre-symmetry set of a surface M in 3-space (resp. smooth closed curve in 2D) is the set of pairs of points which contribute to the symmetry set, that is, the closure …
A novel method compresses point cloud attributes by folding them onto a 2D grid.
problem Efficiently compressing point cloud attributes for storage and transmission.
method Interpreting point clouds as 2D manifolds, folding onto a grid, and mapping attributes to the grid using optimized methods.
result The proposed folding-based approach achieves performance comparable to state-of-the-art codecs.
Study of symmetries in a 2D space with specific metric properties.
problem Understanding symmetries in a 2D space with diagonal metrics.
method Analyzing Killing vector fields under specific restrictions on Lamé coefficients.
result Concretely described symmetries of the metric under given conditions.
Our goal is to provide a novel method of representing 2D shapes, where each shape will be assigned a unique fingerprint - a computable approximation to a conformal map of the given shape to a canonical shape in 2D or 3D space (see page 22 for a few examples). In this paper, we make the first significant step in this pr…
A model for grid cells using vectors and matrices for position and motion.
problem Representing self-position and motion in a high-dimensional space.
method Vector-matrix multiplication, magnified local isometry, and global adjacency kernel.
result The model can learn hexagon patterns and correct errors.
This work improves sampling efficiency on complex spaces using determinantal processes.
problem Efficient sampling from large-scale datasets with general spaces.
method Determinantal point processes on general spaces and diffusion geometry.
result Improved sampling rates for determinantal processes on Riemannian manifolds and networks.
Study bends 2D surfaces in 3D space using special equations.
problem Investigate infinitesimal bendings of 2D surfaces in 3D space.
method Use Bers-Vekua type equations and systems of differential equations with periodic coefficients.
result Construct bending fields for specific classes of 2D surfaces.
Paper studies isoperimetric problem in 2D Finsler space with k=0.
problem Isoperimetric problem in 2D Finsler space with k=0.
method Holmes-Thompson area used to investigate.
result Circle centered at origin achieves maximum area.
New method for optimizing risk in financial models using Fourier transforms.
problem Optimizing risk in financial models with multi-period mean-CVaR.
method Strictly monotone 2D integration scheme via Fourier-trained transition kernels.
result Established robust and accurate optimization method for financial models.
Study 2D spaces with curvature, focusing on structure and approximations.
problem Characterize and understand 2D metric spaces with curvature constraints.
method Lipschitz homotopy approximations, curvature measures, convergence analysis.
result Established Gauss-Bonnet Theorem and characterized spaces.
Projective connection explains gravity dynamics in 2D.
problem Understanding dynamics in 2D gravity with projective connection.
method Using projective connection over affine connections, defining action with curvature invariants.
result Projective connection naturally describes metric interaction in 2D gravity.
Replicable clustering algorithms for k-medians, k-means, and k-centers are proposed.
problem Designing clustering algorithms that produce the same partition on repeated runs under the same distribution.
method Utilizing approximation routines for combinatorial clustering problems in a black-box manner.
result Replicable algorithms for statistical k-medians, k-means, and k-centers with specified approximation and sample complexities. Computes a new metric quantity Y(M) for Riemannian 2d-manifolds.
problem No simple metric quantity exists for Riemannian manifolds.
method Defines Y(M) and Y_disc(M) involving sectional curvatures and computes them for specific manifolds.
result Y(M) and Y_disc(M) differ from the Euler characteristic and can be positive or negative.
This paper proposes grid cells encode position via a conformal isometric embedding of 2D physical space.
problem Hexagonal grid firing patterns in grid cells.
method Learning a distance-preserving position embedding in neural space using a recurrent neural network.
result The conformal isometric embedding of 2D physical space into neural space explains hexagonal grid firing patterns.
The paper develops obstructions for embedding 2D complexes into 4D space.
problem Embedding 2D complexes into 4D space and understanding obstructions.
method Uses Goodwillie-Weiss calculus and intersections of Whitney disks.
result Two approaches to obstructions lead to the same result.
iSTFTNet2 improves iSTFTNet's speed and lightness with 1D-2D CNN.
problem Efficiently synthesizing high-fidelity speech.
method Improved iSTFTNet using 1D-2D CNNs for temporal and spectrogram structures.
result iSTFTNet2 is faster and more lightweight with comparable speech quality.
The conformal Laplacian's algebraic structure is explored in 2D, revealing a central charge.
problem Exploring the algebraic structure of the conformal Laplacian in 2D.
method Using prefactorization algebras and Green functions.
result In 2D, the conformal Laplacian's algebraic structure is revealed through a central charge.
Separates Dirac equation on 2D product spaces and black hole horizons.
problem Separating Dirac equation on complex spacetime backgrounds.
method Used separation of variables in 2D product spaces to solve Dirac equation.
result Dirac equation separable in specific static black hole solutions.
Method generates multiple 3D poses from 2D joint detections, addressing ambiguity and uncertainty.
problem Ambiguity and uncertainty in 3D human pose estimation from 2D joint detections.
method Generative model, compositional, anatomical constraints, removing model bias.
result Generates multiple valid 3D poses consistent with 2D joint detections.
Classifies generic singularities of line fields on 2D manifolds.
problem Classifying singularities of line fields on 2D manifolds.
method Identifying line fields as bisectors of pairs of vector fields, considering singularities as zeros of vector fields, and using a natural topology in the space of pairs of vector fields.
result Generic singularities of line fields on 2D manifolds are topologically equivalent to the Lemon, Star, and Monstar singularities.
Transformer-M learns molecular data in 2D or 3D formats.
problem Learning models for molecules are limited to specific data formats.
method Developed a Transformer-based model that can handle 2D and 3D molecular data.
result Transformer-M achieves strong performance on both 2D and 3D molecular tasks.