Counting tripods on a flat torus using lattice point counting.
arXiv research
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Neuro# learns heuristics to speed up #SAT solvers.
For a geometrically finite group Gamma of G=SO(n,1), we survey recent developments on counting and equidistribution problems for orbits of Gamma in a homogeneous space H\G where H is trivial, symmetric or horospherical. Main applications are found in an affine sieve on orbits of thin groups as well as in sphere countin…
The paper counts mapping classes by Nielsen-Thurston type, finding growth rates for different subsets.
We study the combinatorial geometry of "lattice" Jenkins--Strebel differentials with simple zeroes and simple poles on and of the corresponding counting functions. Developing the results of M. Kontsevich we evaluate the leading term of the symmetric polynomial counting the number of such "lattice" Jenki…
In this paper we consider an elementary, and largely unexplored, combinatorial problem in low-dimensional topology. Consider a real 2-dimensional compact surface , and fix a number of points on its boundary. We ask: how many configurations of disjoint arcs are there on whose boundary is ? We find that thi…
We consider an agent's uncertainty about its environment and the problem of generalizing this uncertainty across observations. Specifically, we focus on the problem of exploration in non-tabular reinforcement learning. Drawing inspiration from the intrinsic motivation literature, we use density models to measure uncert…
Counted essential surfaces in a knot's exterior, finding a unique pattern.
Better neural arithmetic logic units improve cell counting model generalization.
Counting spheres in hyperbolic space with effective methods.
In this paper, we study a new graph learning problem: learning to count subgraph isomorphisms. Different from other traditional graph learning problems such as node classification and link prediction, subgraph isomorphism counting is NP-complete and requires more global inference to oversee the whole graph. To make it …
Counting objects in digital images is a process that should be replaced by machines. This tedious task is time consuming and prone to errors due to fatigue of human annotators. The goal is to have a system that takes as input an image and returns a count of the objects inside and justification for the prediction in the…
Algorithm counts intersections of normal curves efficiently.
Counting the number of clusters, when these clusters overlap significantly is a challenging problem in machine learning. We argue that a purely mathematical quantum theory, formulated using the path integral technique, when applied to non-physics modeling leads to non-physics quantum theories that are statistical in na…
The ability to detect and count certain substructures in graphs is important for solving many tasks on graph-structured data, especially in the contexts of computational chemistry and biology as well as social network analysis. Inspired by this, we propose to study the expressive power of graph neural networks (GNNs) v…
In this paper we study the equidistribution of expanding horospheres in infinite volume geometrically finite rank one locally symmetric manifolds and apply it to the orbital counting problem in apollonian sphere packing.
Multivariate count data are defined as the number of items of different categories issued from sampling within a population, which individuals are grouped into categories. The analysis of multivariate count data is a recurrent and crucial issue in numerous modelling problems, particularly in the fields of biology and e…
Polynomial-time methods count and sample DAGs from equivalence classes.
Graphical estimation of count time series dependencies.
odeN efficiently approximates multiple temporal motifs in large networks.
Complexity of counting group homomorphisms depends on group structure and presentation.
The Poincare function is a compact form of counting moduli in local geometric problems. We discuss its property in relation to V.Arnold's conjecture, and derive this conjecture in the case when the pseudogroup acts algebraically and transitively on the base. Then we survey the known counting results for differential in…
We present the first framework for Gaussian-process-modulated Poisson processes when the temporal data appear in the form of panel counts. Panel count data frequently arise when experimental subjects are observed only at discrete time points and only the numbers of occurrences of the events between subsequent observati…
Flow Matching for count data improves sample quality and efficiency.
Study identifies contagion in aggregated defaults despite environmental changes.
We count meromorphic differentials with fixed residues and poles of fixed orders.
Study counts geodesics on modular surface, linking to necklace counting.
Estimates the number of closed curves on surfaces with power-saving error terms.
From social science to biology, numerous applications often rely on graphlets for intuitive and meaningful characterization of networks at both the global macro-level as well as the local micro-level. While graphlets have witnessed a tremendous success and impact in a variety of domains, there has yet to be a fast and …
We study the problem of counting instantons with coassociative boundary condition in (almost) G_(2)-manifolds. This is analog to the open Gromov-Witten theory for counting holomorphic curves with Lagrangian boundary condition in Calabi-Yau manifolds. We explain its relationship with the Seiberg-Witten invariants for co…
BPNNs learn to solve combinatorial problems faster and more accurately.
Solves nonlinear problems on metric structures through eigenvalue counting.
This work refines Cover's theory for binary classification on low-dimensional data.
Study counts geodesic surfaces in knot complements, finding unique ones for small knots.
New theorem counts curves on orbifolds.
Counting essential surfaces in 3-manifolds yields concise formulae and detailed asymptotics.
Polynomial-time methods count and sample DAGs from Markov classes.
New surgery exact triangles in Heegaard Floer homology for rational slopes.
A new method, Count-MORL, improves offline reinforcement learning by using state-action frequency.
This paper introduces the MCML approach for empirically studying the learnability of relational properties that can be expressed in the well-known software design language Alloy. A key novelty of MCML is quantification of the performance of and semantic differences among trained machine learning (ML) models, specifical…
Proposes a method to reconcile count time series forecasts.
In this paper, a taxonomy for memory networks is proposed based on their memory organization. The taxonomy includes all the popular memory networks: vanilla recurrent neural network (RNN), long short term memory (LSTM ), neural stack and neural Turing machine and their variants. The taxonomy puts all these networks und…
Algorithm recovers permutations of high-dimensional Gaussian vectors with constant correlation.
Automatically counts microglial cells in rat spinal cord images, providing precise counts and uncertainty estimates.
Study geodesic paths on flat surfaces, comparing length and singularity counts.
For every positive, continuous and homogeneous function on the space of currents on a compact surface , and for every compactly supported filling current , we compute as , the number of mapping classes so that . As an application, when the surface in question is close…
Counts arcs in surfaces, proving convergence of geodesic currents.
Deviance-style normalization for sparse, jointly overdispersed count matrices