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arXiv research

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.

169,181 papers · 148 categories

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305989118 · Jun 202019922001200920182026
48 results for mutation clustering

Study links curve singularities to quiver mutations.

problem Understanding the relationship between curve singularities and quiver mutations.
method Investigates the connection between the topology of curve singularities and the mutation equivalence of quivers associated with their morsifications.
result Established a connection between the topology of isolated curve singularities and the mutation equivalence of quivers.

Machine learning clusters mutations in cancer exomes, improving diagnostic speed and cost.

problem Extracting stable mutation structures from cancer exome data for early diagnostics.
method Statistically deterministic machine learning algorithm *K-means applied to exome samples.
result Majority of cancer types exhibit stable mutation clustering, while NMF methods are unstable.

The paper computes presentations of cluster modular groups and verifies their generation by Dehn twists.

problem Computing presentations and verifying generation of cluster modular groups.
method A method to compute presentations of saturated cluster modular groups and verification of generation by cluster Dehn twists.
result The cluster modular groups of specified types are virtually generated by cluster Dehn twists.

The paper defines matrices related to cluster transformations and proves certain quivers have no maximal sequences.

problem Proving quivers associated with once-punctured surfaces do not have maximal green or reddening sequences.
method Defining matrices related to cluster transformations and showing their relationships to the Jacobian and C-matrix.
result Quivers associated with once-punctured surfaces do not have maximal green or reddening sequences.

We generalise surface cluster algebras to the case of infinite surfaces where the surface contains finitely many accumulation points of boundary marked points. To connect different triangulations of an infinite surface, we consider infinite mutation sequences. We show transitivity of infinite mutation sequences on tria…

2017-04-06abs ↗pdf ↗

Paper tackles cancer mutation data challenges by creating useful low-dimensional representations.

problem Challenges in analyzing and using cancer mutation data for classification and clustering.
method Flatsomatic: variational autoencoders (VAEs) to create latent representations of somatic profiles.
result VAE embeddings perform better than PCA for clustering and equally well for classification.

Fixed points found in cluster modular groups under specific conditions.

problem Proving fixed points in cluster modular groups.
method Generalizing Kerckhoff's Nielsen realization theorem for cluster modular groups, using convexity of log-cluster variables.
result Finite subgroups of cluster modular groups have fixed points in cluster manifolds under certain conditions.

Deep generative model for healthcare data identifies coherent substructures and mutational clusters.

problem Analytical challenges in healthcare data, including sparsity, missingness, and small sample sizes.
method Proposes a deep generative Bayesian model with collapsed Gibbs sampling for multinomial count data.
result Identifies coherent substructures and biologically meaningful mutational clusters in cancer data.

We construct finite volume hyperbolic manifolds with large symmetry groups. The construction makes use of the presentations of finite Coxeter groups provided by Barot and Marsh and involves mutations of quivers and diagrams defined in the theory of cluster algebras. We generalize our construction by assigning to every …

2014-09-11abs ↗pdf ↗

Geometrically, Legendrian surfaces related by surgery have related skein-valued cluster spaces.

problem Understanding the skein-valued cluster transformation in Legendrian surfaces.
method Geometric considerations of moduli of holomorphic curves.
result Skein-valued cluster transformation of Legendrian surfaces related by surgery.

In this paper, we study the distribution of the genuses of cluster quivers of finite mutation type. First, we prove that in the 1111 exceptional cases, the distribution of genuses is 00 or 11. Next, we consider the relationship between the genus of an oriented surface and that of cluster quivers from this surface. It…

2014-06-29abs ↗pdf ↗

New knot invariants derived using quantum cluster algebras.

problem Deriving new knot invariants from quantum cluster algebras.
method Interpreting RR-matrix of Uq(sl2)U_q(\mathfrak{sl}_2) as cluster transformation, introducing auxiliary parameter εε.
result Derives perturbed-Alexander invariants with higher-order terms in εε.

A cluster variety of Fock and Goncharov is a scheme constructed by gluing split algebraic tori, called seed tori, via birational gluing maps called mutations. In quantum theory, the ring of functions on seed tori are deformed to non-commutative rings, represented as operators on Hilbert spaces. Mutations are quantized …

2016-02-02abs ↗pdf ↗

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 ↗

Mutation graph of support τ-tilting modules over skew-gentle algebras is connected.

problem Understanding the structure of support τ-tilting modules over skew-gentle algebras.
method Introducing mutation of maximal rigid objects and using exchange triangles to define mutations of support τ-tilting modules.
result The mutation graph of support τ-tilting modules over a skew-gentle algebra is connected.

We construct geometric realization for non-exceptional mutation-finite cluster algebras by extending the theory of Fomin and Thurston to skew-symmetrizable case. Cluster variables for these algebras are renormalized lambda lengths on certain hyperbolic orbifolds. We also compute growth rate of these cluster algebras, p…

2011-11-15abs ↗pdf ↗

Framework uses machine learning to distinguish major COVID-19 variants.

problem Discriminate and visualize associations between major COVID-19 variants based on genome sequences.
method Unsupervised machine learning methods, including k-mer analysis, PCA, t-SNE, UMAP, and agglomerative hierarchical clustering.
result Framework effectively distinguishes between major variants and identifies emerging variants.

Quantum trace maps for surfaces are shown to be compatible under triangulations.

problem Constructing and understanding quantum trace maps for surfaces.
method Developed quantum mutation maps between subalgebras of quantum torus algebras for different triangulations.
result Quantum trace maps are natural and independent of triangulation choices.

We study iteration maps of recurrence relations arising from mutation periodic quivers of arbitrary period. Combining tools from cluster algebra theory and (pre)symplectic geometry, we show that these cluster iteration maps can be reduced to symplectic maps on a lower dimensional submanifold, provided the matrix repres…

2013-07-01abs ↗pdf ↗

The paper proves there are many Lagrangian fillings for Legendrian links of affine type.

problem Proving the existence of many Lagrangian fillings for Legendrian links of affine type.
method Using cluster structures and Coxeter mutation to prove the existence of fillings.
result There are at least as many exact embedded Lagrangian fillings as seeds for Legendrian links of affine type.

We present a global optimization algorithm for clustering data given the ratio of likelihoods that each pair of data points is in the same cluster or in different clusters. To define a clustering solution in terms of pairwise relationships, a necessary and sufficient condition is that belonging to the same cluster sati…

2015-06-09abs ↗pdf ↗

We propose a new description of 3d N=2\mathcal{N}=2 theories which do not admit conventional Lagrangians. Given a quiver QQ and a mutation sequence mm on it, we define a 3d N=2\mathcal{N}=2 theory T[(Q,m)]\mathcal{T}[(Q,m)] in such a way that the Sb3S^3_b partition function of the theory coincides with the cluster partition f…

2013-01-24abs ↗pdf ↗

Study character varieties of surfaces using cluster algebras and Poisson structures.

problem Character varieties of surfaces and their Poisson structures.
method Use Bonahon-Wong's trace map and cluster algebras associated with ideal triangulations.
result Recover Goldman Poisson algebra from cluster algebra structure and show automorphisms.

Genus 2 mutation is the process of cutting a 3-manifold along an embedded closed genus 2 surface, twisting by the hyper-elliptic involution, and gluing back. This paper compares genus 2 mutation with the better-known Conway mutation in the context of knots in the 3-sphere. Despite the fact that any Conway mutation can …

2006-07-11abs ↗pdf ↗

The study finds many Lagrangian fillings for Legendrian links of specific types.

problem Understanding the number and types of Lagrangian fillings for Legendrian links.
method Proved the existence of at least as many exact embedded Lagrangian fillings as seeds for Legendrian links of finite or affine Dynkin type.
result Found many Lagrangian fillings with rotational and conjugation symmetries for specific types of Legendrian links.

Study of machine learning in quiver gauge theories and Seiberg duality.

problem Determining dualities in quiver gauge theories using machine learning.
method Defined and explored various questions related to binary and multi-class duality determination, evaluated performance of different classifiers, and analyzed effects of additional data.
result High accuracy and confidence achieved in determining dualities using machine learning.

Modeling correlated mutations in cancer for personalized treatment.

problem Identifying mutations for personalized cancer therapy in heterogeneous profiles.
method Proposed correlated zero-inflated negative binomial process with mixed beta-Bernoulli and variational inference.
result Identified biologically relevant correlations between somatic mutations.

Flatsomatic compresses cancer mutation data with VAEs, maintaining predictive power.

problem Compressing somatic mutation profiles in cancer while preserving predictive power.
method Flatsomatic uses a Variational Auto Encoder (VAE) with MLP architecture, optimizing evidence lower bound and beta-VAE for latent space regularization.
result Flatsomatic embeddings maintain predictive power of original data, reducing dimensionality from 8,298 to 64.

The paper connects Legendrian links to cluster algebras via microlocal methods.

problem Understanding the relationship between Legendrian links and cluster algebras.
method Microlocal parallel transport of sheaf quantizations of Lagrangian fillings.
result Existence of quasi-cluster A\mathcal{A}-structures and cluster Poisson structures.

Improved genetic programming by optimizing mutation operators for continuous program search.

problem Small syntactic mutations in genetic programming can lead to unpredictable behavioral shifts.
method Learned a compact trading-strategy DSL, created a block-factorized embedding, and designed geometry-compiled mutation operators.
result Geometry-compiled mutation operators discover strong strategies using fewer evaluations and achieve higher Sharpe ratios.

Develops quantum cluster algebra approach to solve tetrahedron equation.

problem Investigates a three-dimensional generalization of the Yang-Baxter equation.
method Quantum cluster algebra approach with realization of quantum Y-variables in terms of q-Weyl algebras.
result Obtains a solution with three spectral parameters and reproduces Sergeev's R matrix.

We define a link homology theory that is readily seen to be both isomorphic to reduced odd Khovanov homology and fully determined by data impervious to Conway mutation. This gives an elementary proof that odd Khovanov homology is mutation invariant, and therefore that mod 2 Khovanov homology is mutation invariant. We a…

2009-03-23abs ↗pdf ↗

Mutation Validation method assesses model fit using mutated training labels without validation sets.

problem Model selection and hyperparameter tuning accuracy in supervised learning.
method Mutation Validation (MV) method using mutated training labels to assess model fit.
result MV provides more accurate model selection and stable hyperparameter tuning results.

We give a new, elementary proof that Khovanov homology with Z/2Z\mathbb{Z}/2\mathbb{Z}--coefficients is invariant under Conway mutation. This proof also gives a strategy to prove Baldwin and Levine's conjecture that δδ--graded knot Floer homology is mutation--invariant. Using the Clifford module structure on $\widetilde…

2017-01-04abs ↗pdf ↗

Mathematician summarizes protein geometry and mutation effects.

problem Understanding how proteins mutate and their structure-function relationship.
method Mathematical analysis of protein structures and functions, focusing on hydrogen bonds and secondary structure.
result Protein secondary structure regulates mutation by stabilizing or destabilizing regions.