Study Vassiliev invariants for virtual knots, expanding quantum theory.
problem Understanding Vassiliev invariants for virtual knots.
method Define chord diagrams, weight systems, and Lie algebra weight systems for rotational virtual knots.
result Extended quantum invariants capture more information than standard invariants.
Improved CNNs for image classification tasks with rotational invariance.
problem Improving CNN performance for tasks with rotation invariance.
method Rotation-equivariant and rotation-invariant encoding using 2D-DFT magnitude responses and efficient convolutional schemes.
result Significant improvement in classification accuracy and robustness to hyperparameters.
Solves scalar curvature equations for rotation invariant Kähler metrics on complex space.
problem Finding rotation invariant Kähler metrics with constant scalar curvature on complex space.
method Reduces the scalar curvature equation to a system of ODEs and solves them.
result Obtains complete lists of rotation invariant metrics with zero or positive scalar curvature in lower dimensions.
GCNNs gain rotation invariance with more training augmentation, making SVD-Universal more effective.
problem Improving robustness of GCNNs to adversarial attacks.
method SVD-Universal technique applied to GCNNs trained with larger rotations.
result SVD-Universal becomes more effective as GCNNs gain rotation invariance.
Overview of methods for rotating 2D and 3D data.
problem Processing data with equivariance/invariance under rotations.
method An overview of methods for 2D and 3D rotations.
result Identification of commonalities and links between methods.
Study real GIT and Wick-rotations of pseudo-Riemannian manifolds.
problem Understanding Wick-rotations and their conditions for pseudo-Riemannian manifolds.
method Extending earlier results, providing sufficient and necessary conditions for Wick-rotatability, and deriving an invariance theorem.
result Derived sufficient and necessary conditions for pseudo-Riemannian manifolds to be Wick-rotatable.
This paper studies rotational virtual knot theory and its relationship with quantum link invariants. Every quantum link invariant for classical knots and links extends to an invariant of rotational virtual knots and links. The paper sets up the background virtual knot theory, defines rotational virtual knot theory, stu…
General rotational surfaces as a source of examples of surfaces in the four-dimensional Euclidean space have been introduced by C. Moore. In this paper we consider the analogue of these surfaces in the Minkowski 4-space. On the base of our invariant theory of spacelike surfaces we study general rotational surfaces with…
A new rotation invariant method for 3D medical imaging classification.
problem Computational expense and lack of rotation invariance in 3D medical image processing.
method Proposes a rotation invariant convolution operator using hypersphere topology.
result Demonstrates improved classification accuracy and rotation invariance.
Paper proposes CNN with SIFT for rotation invariant feature extraction.
problem Max-pooling layer discards rotational information, leading to rotation invariance issues.
method Uses SIFT descriptor to capture orientation and spatial relationships.
result Improves feature extraction on MNIST and fashionMNIST datasets.
Study Wick-rotations of Lie groups using GIT results.
problem Understanding Wick-rotations of pseudo-Riemannian Lie groups.
method Using results from real GIT, analyze invariant metrics and Lie algebras.
result Existence and conjugacy of Cartan involutions for pseudo-Riemannian Lie groups.
Optimal square matrices for image approximation under translation and rotation.
problem Approximating images with translation and rotation invariant subspaces.
method Abstract harmonic analysis for constructing optimal square matrices.
result Optimal approximation of images with minimal quadratic error.
Minimal sets of moves for rotational Reidemeister diagrams are identified.
problem Understanding the minimal sets of moves for rotational Reidemeister diagrams.
method Detailed description and proof of minimal generating sets for rotational Reidemeister moves.
result Minimal generating sets for oriented, framed links contain 5 moves.
We solve Bayesian PCA's rotational symmetry issue by rotation-invariant parameterization.
problem Bayesian PCA's rotational symmetry complicates inference and interpretation.
method Rotation-invariant Householder parameterization using random matrix theory.
result Efficient rotation-invariant probabilistic PCA implementation.
Discuss knots in SgimesS1, introducing rotating information and invariants.
problem Understanding knots in SgimesS1 and their invariants. method Introduce diagrams, moves, and rotating information to construct invariants.
result Construct invariants using the rotating information of knots in SgimesS1. We add prior knowledge to deep networks to make them invariant to transformations.
problem Creating deep networks invariant to transformations like rotation.
method A novel layer based on invariant integration to enforce feature space invariances.
result State-of-the-art performance on the Rotated-MNIST dataset.
Rotation invariant algorithms fail with hard labels sampled from sparse targets.
problem Rotation invariant algorithms fail to learn from hard labels sampled from sparse targets.
method Proving the excess risk of rotation invariant algorithms and proposing a simple non-rotation invariant algorithm.
result Rotation invariant algorithms incur an excess risk of $Ω\left(\frac{d-1}{n}
ight)$, while non-rotation invariant algorithms have an excess risk of $O\left(\frac{s\log d}{n}
ight).
Paper learns to rotate filters for group convolutions.
problem Difficult to rotate 3x3 filters on pixel grids.
method Learn filter basis and rotation-invariant coefficients; switch basis for rotation.
result Produces feature maps insensitive to input rotations.
Paper proves Legendrian knots with same GL-rack have similar invariants.
problem Classifying Legendrian knots based on their invariants.
method Examined fundamental GL-racks and their relationship to Thurston-Bennequin and rotation numbers.
result Two Legendrian knots with isomorphic fundamental GL-racks have similar invariants.
New frame method simplifies solving variational problems with Euclidean symmetry.
problem Solving variational problems with Euclidean symmetry.
method Rotation Minimising frame and symbolic invariant calculus.
result Noether's conservation laws and Euler-Lagrange equations derived directly.
We classify Kähler-Einstein manifolds which admit a Kähler immersion into a finite dimensional complex projective space endowed with the Fubini-Study metric, whose codimention is not greater than 3 and whose metric is rotation invariant.
Rotation invariant algorithms fail on sparse problems even with noise.
problem Rotation invariant algorithms' suboptimality in sparse linear problems with noise.
method Lower bounds and trajectory analysis of optimization algorithms.
result Rotation invariant algorithms are suboptimal even with noise and many examples.
Study invariant λ-translators in Lorentz-Minkowski space.
problem Characterize λ-translators invariant under translations and rotations. method Analyze 1-parameter group of translations and rotations, find explicit parametrizations, and solve non-linear autonomous systems.
result Explicit parametrizations and qualitative properties of invariant λ-translators. Innovates rotation index for matrix pairs, solving group action problems.
problem Solving group actions problems, especially Nielsen realization and higher-rank Anosov actions.
method Rotation index and Milnor--Munkres--Novikov pairing applied to Z2 group actions. result Solved specific group action problems using new matrix pair invariant.
A new transform links rotating calorons to solutions of a differential equation.
problem Existence and characterization of rotating calorons.
method Formulated a Nahm transform to relate rotating calorons to solutions of a delayed-differential equation.
result Existence of an eight-parameter family of rotating calorons with nontrivial holonomy.
Deep nets improve function approximation and learning in high dimensions.
problem Designing neural networks for rotation-invariant function approximation.
method Developed deep neural networks with multiple hidden layers for radial function approximation.
result Deep nets achieve near-optimal function approximation and learning rates not possible by shallow nets.
Graph-based CNN for spherical data with equivariance.
problem Efficiently learning from non-uniformly distributed spherical data.
method Discretized sphere as graph, graph convolutions, equivariance using Defferrard's graph neural network.
result Good performance on rotation-invariant learning problems.
In this paper, we study spacelike rotational surfaces which are called boost invariant surfaces in Minkowski 4-space E41. We give necessary and sufficient condition for flat spacelike rotational surface to have pointwise 1-type Gauss map. Also, we obtain a characterization for boost invariant marginally trapped surface…
High-dimensional kernel regression struggles due to rotational invariance.
problem Kernel ridge regression struggles in high dimensions due to rotational invariance.
method Analysis of kernel properties and their impact on high-dimensional data.
result Lower bound on generalization error for high-dimensional kernel regression.
The paper introduces REQNNs for robust 3D point cloud processing.
problem 3D point cloud processing robustness to rotations.
method Revised neural networks using quaternion features for rotation-equivariance.
result REQNNs exhibit higher rotation robustness compared to original networks.
We give explicit formulas and algorithms for the computation of the rotation number of a nullhomologous Legendrian knot on a page of a contact open book. On the way, we derive new formulas for the computation of the Thurston-Bennequin invariant of such knots and the Euler class and the d3-invariant of the underlying co…
We introduce a novel class of rotation invariants of two dimensional curves based on iterated integrals. The invariants we present are in some sense complete and we describe an algorithm to calculate them, giving explicit computations up to order six. We present an application to online (stroke-trajectory based) charac…
New quadratic forms expand and rotate linear endomorphisms in geometric theory.
problem Understanding the expansion and rotation properties of linear endomorphisms.
method Constructing new quadratic forms based on two-plane rotations.
result Established relations among eigenvalues, eigendirections, and matrix invariants.
The paper classifies invariant translators for a specific curvature flow.
problem Classifying invariant translators for a specific curvature flow.
method Classification of λ-translators invariant under translations and rotations. result All λ-translators are classified. New MCMC method improves sampling efficiency across diverse structural models.
problem Low sampling efficiency in generic MCMC methods for specific problems.
method Adaptive Principal-Component (PC) Meta-learning Stochastic Gradient Hamiltonian Monte Carlo (APM-SGHMC) algorithm.
result Universal samplers achieve zero-shot generalization across structurally distinct models.
A new method estimates target images directly from noisy observations in cryo-EM.
problem Estimating target images from noisy, rotated observations in cryo-EM.
method Estimates rotation-invariant features and then images from these features.
result Effectiveness demonstrated on synthetic cryo-EM datasets.
We study surfaces of constant mean curvature which are invariant by oneparameter group of either rotational isometries or parabolic isometries, immersed into the homogeneous manifold PSL2(R,tau). Also, we give some applications.
Classifies geodesic flows on projective plane with potential field.
problem Classifying geodesic flows on a projective plane with a potential field.
method Liouville classification and calculation of Fomenko--Zieschang invariants.
result All Fomenko--Zieschang invariants of the system are calculated.
In this paper, we determine the maximally stable, rotationally invariant domains on the catenoids $\cC_a$ (minimal surfaces invariant by rotations) in the Heisenberg group with a left-invariant metric. We show that these catenoids have Morse index at least 3 and we bound the index from above in terms of the parameter $…
4-Legendrian permutation racks can't distinguish knots but recover classical invariants.
problem Distinguishing Legendrian knots using permutation racks.
method Study of 4-Legendrian racks and their effectiveness.
result 4-Legendrian permutation racks cannot distinguish knots but recover classical invariants.
In-plane drill rotations are impossible for smooth shells.
problem In-plane drill rotations on smooth shells are impossible.
method Analyzing the differential geometry of surfaces and isometries.
result Any isometry that coincides with the given surface at a portion of the boundary is the identity.
We define Wick-rotations by considering pseudo-Riemannian manifolds as real slices of a holomorphic Riemannian manifold. From a frame bundle viewpoint Wick-rotations between different pseudo-Riemannian spaces can then be studied through their structure groups which are real forms of the corresponding complexified Lie g…
We apply the invariant theory of surfaces in the four-dimensional Euclidean space to the class of general rotational surfaces with meridians lying in two-dimensional planes. We find all minimal super-conformal surfaces of this class.
Solves classical problem with Kähler-Einstein metrics in complex projective spaces.
problem Classical problem of non-isometric bidimensional Kähler-Einstein submanifolds.
method Listed complete non-isometric bidimensional rotation invariant Kähler-Einstein submanifolds.
result Solves the classical problem in the specified case.
Let X be a path-connected topological space admitting a universal cover. Let Homeo(X,a) denote the group of homeomorphisms of X preserving degree one cohomology class a. We investigate the distortion in Homeo(X,a). Let g be an element of Homeo(X,a). We define a Nielsen-type equivalence relation on the space of g-invari…
All knots in R3 possess Seifert surfaces, and so the classical Thurston-Bennequin and rotation (or Maslov) invariants for Legendrian knots in a contact structure on R3 can be defined. The definitions extend easily to null-homologous knots in any 3-manifold M endowed with a contact structure ξ. We generalize…
Translating or rotating an input image should not affect the results of many computer vision tasks. Convolutional neural networks (CNNs) are already translation equivariant: input image translations produce proportionate feature map translations. This is not the case for rotations. Global rotation equivariance is typic…
The study classifies horo-shrinkers in hyperbolic space under different isometries.
problem Characterizing horo-shrinkers in hyperbolic space under various isometries.
method Analyzing horo-shrinkers invariant by one-parameter groups of hyperbolic, parabolic, and spherical isometries.
result Grim reapers are defined as horo-shrinkers invariant by parabolic translations and are periodic surfaces.