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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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17345067 · Jun 202019922001200920182026
48 results for octahedron recurrence

The dimer model and circle patterns are linked via combinatorial and geometric transformations.

problem Understanding the dimer model and its geometric counterpart.
method Established a correspondence between dimer models and circle patterns, using combinatorial and geometric transformations.
result The Miquel dynamics on circle patterns is governed by the octahedron recurrence.

We use the consistency approach to classify discrete integrable 3D equations of the octahedron type. They are naturally treated on the root lattice Q(A3)Q(A_3) and are consistent on the multidimensional lattice Q(AN)Q(A_N). Our list includes the most prominent representatives of this class, the discrete KP equation and its S…

2010-11-15abs ↗pdf ↗

Mazur's knot exterior is described by a single regular ideal octahedron, leading to hyperbolic structures related to the Whitehead link.

problem Proving nonhomeomorphism of boundaries of Mazur and Jester manifolds
method Using hyperbolic geometry, Dehn filling, and systolic geodesics
result Proving the boundaries of all Mazur and Jester manifolds are pairwise nonhomeomorphic

Models for 3D harmonic 1-forms and spinors near singular points.

problem Constructing models for Z/2\mathbb{Z}/2 harmonic 1-forms and spinors in 3D near singular points.
method Using symmetries of tetrahedron, octahedron, and icosahedron to construct local models on R3\mathbb{R}^3.
result Local models are Z/2\mathbb{Z}/2 harmonic 1-forms or spinors on R3\mathbb{R}^3 with zero locus consisting of rays from the origin.

We try to give a cluster algebraic interpretation of complex volume of knots. We construct the R-operator from the cluster mutations, and we show that it is regarded as a hyperbolic octahedron. The cluster variables are interpreted as edge parameters used by Zickert in computing complex volume.

2013-04-17abs ↗pdf ↗

In this article, we describe symplectic and complex toric spaces associated to the five regular convex polyhedra. The regular tetrahedron and the cube are rational and simple, the regular octahedron is not simple, the regular dodecahedron is not rational and the regular icosahedron is neither simple nor rational. We re…

2016-11-30abs ↗pdf ↗

The ratio of volume to crossing number of a hyperbolic knot is known to be bounded above by the volume of a regular ideal octahedron, and a similar bound is conjectured for the knot determinant per crossing. We investigate a natural question motivated by these bounds: For which knots are these ratios nearly maximal? We…

2014-11-28abs ↗pdf ↗

Starting from the (apparently) elementary problem of deciding how many different topological spaces can be obtained by gluing together in pairs the faces of an octahedron, we will describe the central role played by hyperbolic geometry within three-dimensional topology. We will also point out the striking difference wi…

2007-06-29abs ↗pdf ↗

We prove that the 8^4_2 link complement is the minimal volume orientable hyperbolic manifold with 4 cusps. Its volume is twice of the volume V_8 of the ideal regular octahedron, i.e. 7.32... = 2V_8. The proof relies on Agol's argument used to determine the minimal volume hyperbolic 3-manifolds with 2 cusps. We also nee…

2012-09-06abs ↗pdf ↗

The volume density\textit{volume density} of a hyperbolic link KK is defined to be the ratio of the hyperbolic volume of KK to the crossing number of KK. We show that there are sequences of non-alternating links with volume density approaching v8v_8, where v8v_8 is the volume of the ideal hyperbolic octahedron. We show that the…

2015-07-07abs ↗pdf ↗

The study classifies tilings of the sphere by congruent quadrilaterals.

problem Classifying edge-to-edge tilings of the sphere by congruent quadrilaterals.
method Classification of tilings into three classes based on geometric data and parameters.
result Three classes of tilings are identified: 2-layer earth map tilings, quadrilateral subdivisions of the octahedron, and 3-layer earth map tilings.

We prove a rigidity theorem for the geometry of the unit ball in random subspaces of the scl norm in B_1^H of a free group. In a free group F of rank k, a random word w of length n (conditioned to lie in [F,F]) has scl(w)=log(2k-1)n/6log(n) + o(n/log(n)) with high probability, and the unit ball in a subspace spanned by…

2011-04-10abs ↗pdf ↗

We enumerate all spaces obtained by gluing in pairs the faces of the octahedron in an orientation-reversing fashion. Whenever such a gluing gives rise to non-manifold points, we remove small open neighbourhoods of these points, so we actually deal with three-dimensional manifolds with (possibly empty) boundary. There a…

2007-09-10abs ↗pdf ↗

The pullback approach to global Finsler geometry is adopted. Three classes of recurrence in Finsler geometry are introduced and investigated: simple recurrence, Ricci recurrence and concircular recurrence. Each of these classes consists of four types of recurrence. The interrelationships between the different types of …

2016-07-25abs ↗pdf ↗

Study on biharmonic hypersurfaces with specific recurrent operators in Euclidean space.

problem Characterizing biharmonic hypersurfaces with recurrent operators.
method Analysis of various recurrent operators and their impact on biharmonic hypersurfaces.
result Some well-known recurrent operators play a significant role in making biharmonic hypersurfaces minimal.

The aim of the present paper is to investigate new types of recurrence in Finsler geometry, namely, hyper-generalized recurrence and generalized conharmonic recurrence. The properties of such recurrences and their relations to other Finsler recurrences are studied.

2017-07-15abs ↗pdf ↗

To generalize the notion of recurrent manifold, there are various recurrent like conditions in the literature. In this paper we present a recurrent like structure, namely, \textit{super generalized recurrent manifold}, which generalizes both the hyper generalized recurrent manifold and weakly generalized recurrent mani…

2015-04-10abs ↗pdf ↗

Two special Finsler spaces have been introduced and investigated, namely RhR^h-recurrent Finsler space and consircularly recurrent Finsler space. The defining properties of these spaces are formulated in terms of the first curvature tensor of Cartan connection. The following three results constitute the main object of …

2012-05-20abs ↗pdf ↗

The object of the present paper is to obtain the characterization of a warped product semi-Riemannian manifold with a special type of recurrent like structure, called super generalized recurrent. As consequence of this result we also find out the necessary and sufficient conditions for a warped product manifold to sati…

2015-04-13abs ↗pdf ↗

The present paper deals with the proper existence of a generalized class of recurrent manifolds, namely, hyper-generalized recurrent manifolds. We have established the proper existence of various generalized notions of recurrent manifolds. For this purpose we have presented a metric and computed its curvature propertie…

2015-04-10abs ↗pdf ↗

We present explicit geometric decompositions of the complement of tiling links, which are alternating links whose projection graphs are uniform tilings of the 2-sphere, the Euclidean plane or the hyperbolic plane. This requires generalizing the angle structures program of Casson and Rivin for triangulations with a mixt…

2016-03-11abs ↗pdf ↗

Interneurons improve learning in neural networks by accelerating convergence.

problem Rapid adaptation to changing input statistics in neural networks.
method Two mathematically tractable recurrent linear neural networks were compared: one with direct recurrent connections and the other with interneurons that mediate recurrent communication.
result The network with interneurons converges more quickly than the network with direct recurrent connections, scaling logarithmically with initialization spectrum.

Unified recurrent networks reveal differences in complexity levels of grammars.

problem Understanding the complexity and behavior of recurrent networks.
method Connecting recurrent networks with deterministic finite automata and formal grammars.
result Unified recurrent networks improve performance and match grammars from different complexity levels.

Study predicts colorectal polyp recurrence using medical records and statistical models.

problem Identifying patient characteristics influencing colorectal polyp recurrence.
method Natural language processing for extracting polyp characteristics, Kaplan-Meier curves, Cox proportional hazards modeling, random survival forest models.
result Polyp size, number, location, and patient smoking status significantly influence recurrence risk.

Enhanced speech emotion recognition using nonlinear recurrence dynamics.

problem Improving speech emotion recognition accuracy.
method Phase space reconstruction, Recurrence Plot, Recurrence Quantification Analysis, statistical functionals, feature fusion, Bidirectional Recurrent Neural Network.
result State-of-the-art performance on IEMOCAP with up to 10.7% improvement in accuracy.

Recurrent-DBN models dynamic relational data with interpretable latent structures.

problem Interpreting dynamic relational data with hidden structures.
method Recurrent Dirichlet Belief Network framework with hierarchical latent structures and efficient inference strategy.
result Recurrent-DBN discovers interpretable latent structures and improves link prediction.

In this paper we adopt the pullback approach to global Finsler geometry. We investigate horizontally recurrent Finsler connections. We prove that for each scalar (ππ)1-form AA, there exists a unique horizontally recurrent Finsler connection whose hh-recurrence form is AA. This result generalizes the existence and u…

2017-06-19abs ↗pdf ↗

Stability is a fundamental property of dynamical systems, yet to this date it has had little bearing on the practice of recurrent neural networks. In this work, we conduct a thorough investigation of stable recurrent models. Theoretically, we prove stable recurrent neural networks are well approximated by feed-forward …

2018-05-25abs ↗pdf ↗

The study of Platonic solids' unfoldings leads to high genus Teichmüller curves.

problem Understanding the topology and geometry of Teichmüller curves from Platonic solids.
method Computing Teichmüller curves using lattice surfaces and algorithmic approaches.
result The Teichmüller curve of the unfolded dodecahedron has genus 131 with specific singularities and cusps.

Transformer models outperform recurrent ones in modeling hierarchical data.

problem Modeling hierarchical structure in data.
method Introducing Multiresolution Transformer Networks leveraging self-attention.
result Multiresolution Transformer Networks significantly outperform state-of-the-art models on query suggestion datasets.

This paper analyzes the generalization risk of unrolled neural networks using Stein's Unbiased Risk Estimator.

problem Analyzing the generalization risk of unrolled neural networks and its relationship to network design and train sample size.
method Using Stein's Unbiased Risk Estimator (SURE), the paper analyzes the generalization risk with bias and variance components for recurrent unrolled networks, focusing on the degrees-of-freedom (DOF) component and the trace of the end-to-end network Jacobian.
result DOF is well-approximated by the weighted path sparsity of the network under incoherence conditions on the trained weights, and DOF increases with train sample size and converges to the generalization risk for both recurrent and non-recurrent schemes.

The study broadens the concept of cyclic polytopes to Veronese polytopes.

problem Extending the framework of cyclic polytopes to a broader class of polytopes.
method Described facial structure and combinatorial characterisation of facets via σ-parity alternating sequences.
result Established a bijective correspondence between combinatorial types of Veronese polytopes and partitions of finite sets.

Recurrent neural networks improve time series forecasting accuracy.

problem Time series forecasting is challenging, especially for sequential data.
method A recurrent neural network framework for feature engineering, prediction, and evaluation is presented.
result The LSTM and GRU networks outperform traditional methods in forecasting accuracy.

RecNets use RNNs to process image channels in a compact, recurrent way.

problem Creating efficient neural network architectures for computer vision.
method Introducing RecNets with CRC layers that simulate recurrent processing of image channels.
result RecNets achieve superior size-accuracy trade-off compared to other compact models.

In this paper, we prove that evry 3-dimensional manifold M is a ?- recurrent N(k)-contact metric manifold if and only if it is flat. Then we classify the ?-recurrent contact metric manifolds of constant curvature. This implies that there exists no ?-recurrent N(k)-contact metric manifold, which is neither symmetric nor…

2013-02-16abs ↗pdf ↗