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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.

169,051 papers · 148 categories

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48 results for interpretable hierarchies

Symmetry reduction of Painlevé IV to Flaschka-Newell Painlevé II

problem Isomonodromic deformation problem associated with rank-two meromorphic connections
method Symmetry Ψ(λ)=σ1Ψ(λ)σ1Ψ(-λ)= σ_1 Ψ(λ) σ_1
result Induced isomonodromic dynamics coincides with Flaschka-Newell Painlevé II hierarchy

Concept Hierarchies and Formal Concept Analysis are theoretically well grounded and largely experimented methods. They rely on line diagrams called Galois lattices for visualizing and analysing object-attribute sets. Galois lattices are visually seducing and conceptually rich for experts. However they present important…

2013-03-11abs ↗pdf ↗

Proposes a hierarchical curriculum loss to improve model accuracy and interpretability.

problem Flat label spaces in classification algorithms fail to capture dependencies in real-world data.
method Introduces hierarchical curriculum loss with two properties: satisfying hierarchical constraints and providing non-uniform label weights.
result The proposed loss function significantly outperforms multiple baselines on real-world image datasets.

RICH models scenes as hierarchical tree to learn and generate complex compositions.

problem Learning compositional structures between parts and objects in natural scenes.
method RICH uses a latent scene graph to organize entities into a tree structure and employs a top-down inference approach.
result RICH learns and generates complex scene hierarchies from unlabeled data.

Proposes a new multi-layer model for topic distributions.

problem Leveraging deep structures for learning word distributions of topics.
method A multi-layer generative process on word distributions of topics, where each topic is drawn from a mixture of topics from the layer above.
result Discover interpretable topic hierarchies and improve topic models' accuracy and interpretability.

This work proposes a new method to train models with deep latent hierarchies using Optimal Transport.

problem Training models with deep latent hierarchies using VAEs often leads to the 'latent variable collapse' issue.
method Proposes a novel approach based on Optimal Transport to train models with deep latent hierarchies.
result The method avoids the 'latent variable collapse' issue and provides better sample generations and latent representation.

This paper develops a cohomological hierarchy for bistable visual paradoxes.

problem Understanding the hierarchy of visual paradoxes built from bistable elements.
method Develops a cohomological hierarchy using Z2\mathbb{Z}_2 coefficients and a discrete Stokes theorem.
result Reveals a hierarchy of paradox classes from H0H^0 through H2H^2, refined at each degree by the relative/absolute distinction.

In this paper we investigate flows on discrete curves in $\C^2$, $\CP^1$, and $\C$. A novel interpretation of the one dimensional Toda lattice hierarchy and reductions thereof as flows on discrete curves will be given.

2002-08-23abs ↗pdf ↗

Starting from the vortex filament flow introduced in 1906 by Da Rios, there is a hierarchy of commuting geometric flows on space curves. The traditional approach relates those flows to the nonlinear Schrödinger hierarchy satisfied by the complex curvature function of the space curve. Rather than working with this infin…

2018-09-05abs ↗pdf ↗

New methods prune unpromising rules from KGs, improving scalability and runtime.

problem Scalability issues in walk-based rule learning from KGs.
method Rule Hierarchy Framework (RHF) and Hierarchical Pruning (HPMs).
result Significant reductions in runtime and number of learned rules without compromising predictive performance.

Decomposes financial networks to reveal cause-effect hierarchies during crises.

problem Complex financial networks are hard to interpret due to Granger causality.
method Helmholtz-Hodge-Kodaira decomposition to separate networks into rotational and gradient components.
result Precious metals and pharmaceutical products are identified as causal drivers during crises.

Deep neural networks (DNNs) have achieved impressive predictive performance due to their ability to learn complex, non-linear relationships between variables. However, the inability to effectively visualize these relationships has led to DNNs being characterized as black boxes and consequently limited their application…

2018-06-14abs ↗pdf ↗

TRAM-DAG models bridge interpretability and flexibility in causal modeling.

problem Modeling causal relationships in diverse data types while maintaining interpretability.
method Using transformation models (TRAMs) within structural causal models (SCMs) to handle various data types and maintain interpretability.
result TRAM-DAG models achieve equal or superior performance in causal queries across different levels of the causal hierarchy.

Constructs integrable hierarchies for generalized Frobenius manifolds with non-flat unity.

problem Integrable hierarchies for generalized Frobenius manifolds with non-flat unity.
method Constructs a bihamiltonian integrable hierarchy of hydrodynamic type.
result Integrable hierarchy possesses Virasoro symmetries and a tau structure.

Introduces a probabilistic view of deep learning for better understanding and explaining neural networks.

problem Explaining the behavior and properties of deep neural networks.
method Introduces a probabilistic representation of deep learning, linking neurons, hidden layers, and the whole architecture to Gibbs distributions and Bayesian neural networks.
result Demonstrates the hierarchy and generalization properties of deep learning through a probabilistic lens.

We present a novel method for hierarchical topic detection where topics are obtained by clustering documents in multiple ways. Specifically, we model document collections using a class of graphical models called hierarchical latent tree models (HLTMs). The variables at the bottom level of an HLTM are observed binary va…

2016-05-21abs ↗pdf ↗

Study identifies pitfalls in assessing hierarchies for multi-class classification.

problem Lack of understanding in selecting hierarchies for multi-class classification.
method Analyzed and compared popular approaches to extracting hierarchies.
result Hierarchy quality becomes irrelevant when using powerful classifiers.

This paper goes some way in explaining how to construct an integrable hierarchy of flows on the space of conformally immersed tori in n-space. These flows have first occured in mathematical physics -- the Novikov-Veselov and Davey-Stewartson hierarchies -- as kernel dimension preserving deformations of the Dirac operat…

2001-11-14abs ↗pdf ↗

Legendre transformations link related integrable hierarchies.

problem Understanding relationships between integrable hierarchies.
method Legendre-type transformations of generalized Frobenius manifolds.
result Linear reciprocal transformations link related hierarchies.

Twisted UU- and twisted U/KU/K-hierarchies are soliton hierarchies introduced by Terng to find higher flows of the generalized sine-Gordon equation. Twisted O(J,J)O(J)×O(J)\frac {O(J,J)}{O(J)\times O(J)}-hierarchies are among the most important classes of twisted hierarchies. In this paper, interesting first and higher flows of twi…

2011-03-31abs ↗pdf ↗

We propose a formally completely integrable extension of heat hierarchy based on the space of symmetries isomorphic to the Weyl algebra A1\mathcal{A}_1. The extended heat hierarchy will be the basic model for the analysis of the extension of KP hierarchy, and other integrable equations.

2014-01-19abs ↗pdf ↗

New hierarchies derived from KP hierarchy using non-formal operators and Yang-Mills action.

problem Formal solutions of KP hierarchy and their non-formal counterparts.
method Developed new hierarchies of non-linear equations on non-formal pseudo-differential operators.
result Expressed one hierarchy as Yang-Mills action minimization.

Scroll structures on solutions of 4D integrable equations are involutive and governed by a dispersionless hierarchy.

problem Characterizing the geometry of solutions to 4D integrable equations.
method Defining rational normal scrolls and showing their involutivity.
result Involutive scroll structures are governed by a dispersionless integrable hierarchy.

Constructs tri-Hamiltonian structure and Frobenius manifold for asymmetric gAL hierarchy

problem Tri-Hamiltonian structure and Frobenius manifold for asymmetric gAL hierarchy
method Local tri-Hamiltonian structure construction and Frobenius manifold construction
result Dispersionless limits of flows belong to Principal Hierarchy

A relation between the Goldstein-Petrich hierarchy for plane curves and the Toda lattice hierarchy is investigated. A representation formula for plane curves is given in terms of a special class of ττ-functions of the Toda lattice hierarchy. A representation formula for discretized plane curves is also discussed.

2013-10-26abs ↗pdf ↗

HAKE embeds entities in polar coordinates to model semantic hierarchies in knowledge graphs.

problem Lack of modeling semantic hierarchies in knowledge graph embeddings.
method HAKE embeds entities in a polar coordinate system, where the radial coordinate represents hierarchy levels and the angular coordinate distinguishes entities at the same level.
result HAKE significantly outperforms existing methods on link prediction tasks in knowledge graphs.

New integrable deformations for topological hierarchies from Frobenius manifolds.

problem Integrable deformations of topological hierarchies from Frobenius manifolds.
method Construction of integrable deformations with polynomial tau-structures.
result Conjecture of universal object for Riemann--Hopf hierarchy.

We introduce two families of soliton hierarchies: the twisted hierarchies associated to symmetric spaces. The Lax pairs of these two hierarchies are Laurent polynomials in the spectral variable. Our constructions gives a hierarchy of commuting flows for the generalized sine-Gordon equation (GSGE), which is the Gauss-Co…

2010-10-27abs ↗pdf ↗

Paper investigates methods to improve classification by inducing a hierarchy from flat labels.

problem Improving classification performance on datasets lacking a natural hierarchy.
method The approach involves clustering conditional distributions and using a hierarchical classifier with the induced hierarchy.
result The methods can discover latent hierarchies and improve accuracy in various applications.

Framework harmonizes EHR data across institutions for better analysis.

problem Heterogeneity of medical codes and terminologies hinder EHR data analysis.
method MASH (Multi-source Automated Structured Hierarchy) uses neural optimal transport and learned hyperbolic embeddings to align and structure EHR data.
result MASH generates interpretable hierarchical graphs for unstructured local laboratory codes.

We prove that the extended Toda hierarchy of \cite{CDZ} admits nonabelian Lie algebra of infinitesimal symmetries isomorphic to the half of the Virasoro algebra. The generators LmL_m, m1m\geq -1 of the Lie algebra act by linear differential operators onto the tau function of the hierarchy. We also prove that the tau fu…

2003-08-15abs ↗pdf ↗

Paper addresses limitations of traditional hierarchical clustering methods.

problem Traditional hierarchical clustering methods face limitations in binary trees and ultrametrics.
method Introduces the notion of a valid hierarchy and a two-step algorithm to construct a binary tree and prune it to enforce validity.
result Proposes a method to recover the finest valid hierarchy, which is not constrained to binary structures.