arXiv research

Determinants of theta curves and symmetric graphs are studied.

In this paper, we propose a probabilistic parsing model, which defines a proper conditional probability distribution over non-projective dependency trees for a given sentence, using neural representations as inputs. The neural network architecture is based on bi-directional LSTM-CNNs which benefits from both word- and …

Paper derives a formula for the determinant of Dirichlet-to-Neumann operator on Riemann surfaces.

The spectral geometry of mesh matrices of graphs is explored, leading to new formulas and eigenvalue estimates.

The classical Matrix-Tree Theorem allows one to list the spanning trees of a graph by monomials in the expansion of the determinant of a certain matrix. We prove that in the case of three-graphs (that is, hypergraphs whose edges have exactly three vertices) the spanning trees are generated by the Pfaffian of a suitably…

Bicycle paths form geodesics in 3D subspaces, related to Kirchhoff rods.

By a theorem of Kirchhoff if the six sphere admits an almost complex structure then the seven sphere is parallelizable, more crucial, he exhibited an explicit global frame constructed out of the given almost complex structure. This result implicitly equips the seven sphere with a definite H-space multiplication. We pro…

This talk is a report on joint work with A. Vaintrob [arXiv:math.CO/0109104 and math.GT/0111102]. It is organised as follows. We begin by recalling how the classical Matrix-Tree Theorem relates two different expressions for the lowest degree coefficient of the Alexander-Conway polynomial of a link. We then state our fo…

Introduces Lax-Kirchhoff moduli spaces for quivers and Lie groups.

Knot Theory is currently a very broad field. Even a long survey can only cover a narrow area. Here we concentrate on the path from Goeritz matrices to quasi-alternating links. On the way, we often stray from the main road and tell related stories, especially if they allow as to place the main topic in a historical cont…

SHAKE-GNN scales GNNs for large graphs with multi-scale representations.

Kirchhoff energy is a classical functional on the space of arclength-parameterized framed curves whose critical points approximate configurations of springy elastic rods. We introduce a generalized functional on the space of framed curves of arbitrary parameterization, which model rods with axial stretch or cross-secti…

Study p-Willmore disks with boundary energies, finding equilibrium configurations.

Develops control and observer methods for complex systems.

The paper explores variational problems on Riemannian manifolds with special foliations, proving existence results.

Extends classical results to virtual links, proving new properties of alternating and semi-alternating virtual links.

New approach links 2D fluid dynamics to matrix theory.

Bayesian learning for forests and trees improves graph detection and structure learning.

A Bayesian treatment of latent directed graph structure for non-iid data is provided where each child datum is sampled with a directed conditional dependence on a single unknown parent datum. The latent graph structure is assumed to lie in the family of directed out-tree graphs which leads to efficient Bayesian inferen…

Theory of point vortices extended to closed surfaces.

New sigma models compute graviton scattering amplitudes from quaternionic geometry.

Decision Machines embeds decision trees into vector spaces for improved optimization.

Recently V. Krushkal and D. Renardy generalized the Tutte polynomial from graphs to cell complexes. We show that evaluating this polynomial at the origin gives the number of cellular spanning trees in the sense of A. Duval, C. Klivans, and J. Martin. Moreover, after a slight modification, the Tutte-Krushkal-Renardy pol…

SNJ recovers latent tree models from similarity matrices.

New approach to electric group for knots and links.

We discuss some methods to quantitatively investigate the properties of correlation matrices. Correlation matrices play an important role in portfolio optimization and in several other quantitative descriptions of asset price dynamics in financial markets. Specifically, we discuss how to define and obtain hierarchical …

We consider the inference of the structure of an undirected graphical model in an exact Bayesian framework. More specifically we aim at achieving the inference with close-form posteriors, avoiding any sampling step. This task would be intractable without any restriction on the considered graphs, so we limit our explora…

Study of discrete period matrices on embedded graphs, relating to Riemann surfaces.

Introduces a theorem for groups acting on trees.

MFAI uses gradient boosted trees to leverage auxiliary info for scalable Bayesian matrix factorization.

Paper proves conditions for estimating precision matrices with Laplacian constraints.

In this paper, we present a general, multistage framework for graphical model approximation using a cascade of models such as trees. In particular, we look at the problem of covariance matrix approximation for Gaussian distributions as linear transformations of tree models. This is a new way to decompose the covariance…

We study a notion of deformation for simplicial trees with group actions (G-trees). Here G is a fixed, arbitrary group. Two G-trees are related by a deformation if there is a finite sequence of collapse and expansion moves joining them. We show that this relation on the set of G-trees has several characterizations, in …

Paper proposes an algorithm to reconstruct optimal model structure from graph adjacency matrix.

Consider jointly Gaussian random variables whose conditional independence structure is specified by a graphical model. If we observe realizations of the variables, we can compute the covariance matrix, and it is well known that the support of the inverse covariance matrix corresponds to the edges of the graphical model…

This work introduces a novel nonparametric density index defined on graphs, the Sum-over-Forests (SoF) density index. It is based on a clear and intuitive idea: high-density regions in a graph are characterized by the fact that they contain a large amount of low-cost trees with high outdegrees while low-density regions…

We prove an acylindrical accessibility theorem for finitely generated groups acting on $\mathbf R$-trees. Namely, we show that if $G$ is a freely indecomposable non-cyclic $k$-generated group acting minimally and $M$-acylindrically on an $\mathbf R$-tree $X$ then for any $ε>0$ there is a finite subtree $Y_ε\subseteq X$…

Positive-curvature metrics on trees identified for specific configurations.

This paper clarifies vine copula structures using graph and matrix representations.

Linear algebra algorithms are used widely in a variety of domains, e.g machine learning, numerical physics and video games graphics. For all these applications, loop-level parallelism is required to achieve high performance. However, finding the optimal way to schedule the workload between threads is a non-trivial prob…

The study investigates kernel-target alignment in tree ensemble kernels.

CEDA analyzes large categorical datasets using tree geometry and binary codes.

Semi-analytic models are best suited to compare galaxy formation and evolution theories with observations. These models rely heavily on halo merger trees, and their realistic features (i.e., no drastic changes on halo mass or jumps on physical locations). Our aim is to provide a new framework for halo merger tree gener…

Existence and uniqueness of discrete Einstein metrics on trees proven.

In this paper we develop a bubble tree structure for a degenerating class of Riemannian metrics satisfying some global conformal bounds on compact manifolds of dimension 4. Applying the bubble tree structure, we establish a gap theorem, a finiteness theorem for diffeomorphism type for this class, and a diameter bound f…

Physics-guided neural network improves power flow analysis.

This paper proves a Faber-Krahn inequality for trees with given matching number.

Infinite BART model selects number of trees and allows different functions for clusters.