Neural execution solves complex graph problems like bipartite matching.
problem Solving complex graph algorithms like maximum bipartite matching.
method Reduces bipartite matching to a flow problem and uses Ford-Fulkerson for maximum flow.
result Neural network achieves optimal matching almost 100% of the time.
Discrete flows extend normalizing flows to discrete data, improving various applications.
problem Applying normalizing flows to discrete data distributions.
method Developed discrete autoregressive and bipartite flows, showing their effectiveness on various discrete data tasks.
result Discrete autoregressive flows outperform autoregressive baselines on synthetic discrete distributions and Potts models.
Study explores properties of bipartite knots.
problem None explicitly stated; focuses on properties of bipartite knots.
method Exploration of combinatorial structure.
result Rich combinatorial structure of bipartite knots.
New method extends knot theory to non-bipartite knots, revealing PDs.
problem Extending knot theory to non-bipartite knots.
method Developed a new positive decomposition (PD) for HOMFLY polynomials of non-bipartite knots.
result PD exists for non-bipartite knots, not just bipartite ones.
Simplified Khovanov polynomials for bipartite links.
problem Computing Khovanov polynomials for bipartite links.
method Reduced Khovanov-Rozansky technique to Kauffman-Khovanov cycle calculus.
result Consistency demonstrated between reduced technique and bipartite Khovanov polynomials.
Bipartite networks are a common type of network data in which there are two types of vertices, and only vertices of different types can be connected. While bipartite networks exhibit community structure like their unipartite counterparts, existing approaches to bipartite community detection have drawbacks, including im…
New model for detecting communities in weighted bipartite networks.
problem Lack of models for weighted bipartite networks.
method Introducing Bipartite Distribution-Free model and its extension.
result Spectral algorithms for consistent estimation of node labels.
Bipartite graphs with more edges than a threshold have positive curvature.
problem Determining the curvature of bipartite graphs based on edge density.
method Using a new formula for Lin--Lu--Yau curvature, the study establishes conditions for bipartite graphs to have positive curvature.
result Bipartite graphs with more edges than the specified threshold have positive Lin--Lu--Yau curvature.
Cascade-BGNN efficiently learns node representations for large-scale bipartite graphs.
problem Efficiently learning node representations for large-scale bipartite graphs with limited labels.
method Cascade-BGNN uses customized Inter-domain Message Passing (IDMP) and Intra-domain Alignment (IDA) for efficient information aggregation.
result Cascade-BGNN achieves domain-consistent, self-supervised, and efficient node representation learning.
New research finds six bipartite intrinsically knotted graphs with 23 edges.
problem Identifying intrinsically knotted bipartite graphs with 23 edges.
method Analyzing embeddings and graph minors to find minimal intrinsically knotted graphs.
result No minor minimal intrinsically knotted bipartite graph exists with 23 edges.
Simplified Khovanov-Rozansky calculus for bipartite knots.
problem Complexity in calculating superpolynomials for knots.
method Bipartite calculus generalizes Khovanov-Rozansky calculus for a restricted class of knots.
result Simplification of Khovanov-Rozansky polynomials for bipartite knots.
Proves Khovanov homology has no torsion for bipartite circle graphs.
problem Proving properties of Khovanov homology for bipartite circle graphs.
method Proved homotopy equivalence of independence complexes to wedges of spheres.
result Extreme Khovanov homology has no torsion.
Improved bipartite link prediction using 2-hop paths.
problem Link prediction in bipartite networks without node attributes.
method Multiply reconstructed adjacency matrix with symmetrically normalized training adjacency matrix to form 2-hop paths.
result 2-hop paths improve link prediction performance.
New model for detecting communities in weighted bipartite networks.
problem No model for community detection in overlapping bipartite weighted networks.
method Introduces BiMMDF model allowing any distribution with block structure.
result Efficient algorithm with theoretical guarantee of consistent estimation.
A new method calculates HOMFLY-PT polynomials for bipartite links.
problem Computing HOMFLY-PT polynomials for bipartite links efficiently.
method Generalizes Goeritz matrix method for bipartite links.
result Reduces HOMFLY-PT polynomial calculation to matrix algebra.
We define integral odd Khovanov homology of principally unimodular bipartite graph-links.
A new SBM for bipartite networks improves community detection in noisy data.
problem Community detection in bipartite networks with stochastic blockmodels.
method Bayesian nonparametric formulation of SBM for bipartite networks, algorithm to find communities efficiently.
result Improves community detection results over general SBMs, especially in noisy data.
PAC learning simplified as bipartite matching.
problem Efficiently solving PAC learning problems.
method Transductive learning and one-inclusion graphs.
result PAC learning can be reduced to bipartite matching.
We present a simple combinatorial model for quasipositive surfaces and positive braids, based on embedded bipartite graphs. As a first application, we extend the well-known duality on standard diagrams of torus links to twisted torus links. We then introduce a combinatorial notion of adjacency for bipartite graph links…
We present evidence in support of a conjecture that a bipartite graph with at least five vertices in each part and |E(G)| \geq 4 |V(G)| - 17 is intrinsically knotted. We prove the conjecture for graphs that have exactly five or exactly six vertices in one part. We also show that there is a constant C_n such that a bipa…
Develops a new variational estimator for node popularity in bipartite networks.
problem Estimating node popularity in bipartite networks with varying patterns.
method Variational Expectation-Maximization (VEM) framework for the Two-Way Node Popularity Model (TNPM).
result The proposed method achieves superior estimation accuracy across different types of networks.
Improved text summarization using belief propagation on weighted bipartite graphs.
problem Text summarization from a graph theory perspective.
method Generalized belief propagation algorithm for weighted bipartite graphs.
result Our algorithm outperforms greedy methods in text summarization tasks.
Researchers compute connectivity of braid group in bipartite graph configuration space.
problem Understanding connectivity of braid group in complex configuration space.
method Analysis of topology, hidden symmetry, and literature results.
result Explicit computation of connectivity at infinity for braid group.
New method for matching bipartite and unipartite graphs without collapsing.
problem Matching between bipartite and unipartite networks without losing information.
method Formulated as an undirected graphical model, aligns graphs without collapsing.
result Consistent method with conditions for exact recovery of matching solution.
Incorrect parity-based descriptions of realizable Gauss diagrams found, but bipartite graphs provide a valid approach.
problem Incorrect descriptions of realizable Gauss diagrams using parity conditions.
method Used bipartite graphs to describe realizable Gauss diagrams.
result Realizable Gauss diagrams can be accurately described using bipartite graphs.
Bipartite Riemann-Finsler geometries with complementary Finsler structures are constructed. Calculable examples are presented based on a bilinear-form coefficient for explicit Lorentz violation.
New method for calculating HOMFLY polynomials in symmetric representations.
problem Calculating HOMFLY polynomials for symmetric representations.
method Planar decomposition and projection to symmetric representations.
result Restoration of planarity and new insights into HOMFLY polynomials.
A new model detects common patterns in pollination networks.
problem Comparing organization of bipartite networks to understand community structure.
method colBiSBM, a family of probabilistic models for collections of bipartite networks.
result The method uncovers shared ecological roles and partitions networks.
We characterize which automorphisms of an arbitrary complete bipartite graph Kn,m can be induced by a homeomorphism of some embedding of the graph in S3.
A graph is intrinsically knotted if every embedding contains a knotted cycle. It is known that intrinsically knotted graphs have at least 21 edges and that the KS graphs, K7 and the 13 graphs obtained from K7 by ∇Y moves, are the only minor minimal intrinsically knotted graphs with 21 edges. This set incl…
The symmetries of complex molecular structures can be modeled by the {\em topological symmetry group} of the underlying embedded graph. It is therefore important to understand which topological symmetry groups can be realized by particular abstract graphs. This question has been answered for complete graphs; it is natu…
New tests detect communities in dense bipartite graphs with high accuracy.
problem Detecting communities in dense bipartite graphs with high accuracy.
method Non-asymptotic upper and lower bounds, novel minimax-optimal tests, hard-thresholded nonlinear statistics.
result Non-asymptotic upper and lower bounds match for any configuration of graph sizes.
We study the Thurston-Bennequin number of complete and complete bipartite Legendrian graphs. We define a new invariant called the total Thurston-Bennequin number of the graph. We show that this invariant is determined by the Thurston-Bennequin numbers of 3-cycles for complete graphs and by the Thurston-Bennequin number…
The interior polynomial is an invariant of (signed) bipartite graphs, and the interior polynomial of a plane bipartite graph is equal to a part of the HOMFLY polynomial of a naturally associated link. The HOMFLY polynomial PL(v,z) is a famous link invariant with many known properties. For example, the HOMFLY polynom…
Paper presents a low-cost algorithm for bipartite ranking with improved sample size requirements.
problem Bipartite ranking's quadratic dependence on sample size makes it computationally expensive.
method Uses a novel uniform risk bound based on matrix and vector concentration inequalities to achieve low cost and competitive performance.
result Shows that the sample size required for competitive performance is not quadratic, improving efficiency.
In this paper we analyse the bipartite Colombian firms-products network, throughout a period of five years, from 2010 to 2014. Our analysis depicts a strongly modular system, with several groups of firms specializing in the export of specific categories of products. These clusters have been detected by running the bipa…
Positive Thompson links are arborescent tangles.
problem Understanding the structure of Thompson group elements.
method Analyzing closures of bipartite arborescent tangles.
result Positive Thompson links correspond to arborescent tangles.
New explicit constructions of unbalanced Ramanujan bipartite graphs.
problem Constructing bipartite Ramanujan graphs with specified degrees and avoiding certain edges.
method Presented explicit constructions and discussed known methods for Ramanujan graph construction.
result Affirmative answer to constructing unbalanced Ramanujan bipartite graphs under certain conditions.
Proposes new embeddings for bipartite graphs to better capture indirect relationships.
problem Typical graph embeddings fail to capture type-specific features in bipartite graphs.
method Develops two types of embeddings (FOBE and HOBE) that decompose edges into indirect relationships and uses algebraic distance for higher-order sampling.
result Ensemble embeddings improve performance over individual methods in link prediction and recommendation tasks.
Temperley-Lieb algebras have been generalized to sl(3) web spaces. Since a cubic bipartite planar graph with suitable directions on edges is a web, the quantum sl(3) invariants naturally extend to all cubic bipartite planar graphs. First we completely classify them as a connected sum of primes webs. We also provide a m…
We determine for which n, the complete bipartite graph Kn,n has an embedding in S3 whose topological symmetry group is isomorphic to one of the polyhedral groups: A4, A5, or S4.
The interior polynomial is an invariant of bipartite graphs, and a part of the HOMFLY polynomial of a special alternating link coincides with the interior polynomial of the Seifert graph of the link. We extend the interior polynomial to signed bipartite graphs, and we show that, in the planar case, it is equal to a par…
We introduce a new invariant of bipartite chord diagrams and use it to construct the first examples of groups with Dehn function n2logn and other small Dehn functions. Some of these groups have undecidable conjugacy problem.
New algorithm uses imperfect advice to improve online bipartite matching performance.
problem Online bipartite matching with imperfect advice.
method Designing an algorithm that uses external advice to improve performance between advice-free methods and optimal ratio.
result Algorithm achieves competitive ratio interpolating between advice-free methods and optimal ratio of 1.
Improved model for grouping nodes in bipartite networks.
problem Challenges in grouping nodes in bipartite graphs.
method Introduced DC-LBM and developed variational EM algorithm.
result Significantly enhanced performance on real-world data.
The problem of bipartite ranking, where instances are labeled positive or negative and the goal is to learn a scoring function that minimizes the probability of mis-ranking a pair of positive and negative instances (or equivalently, that maximizes the area under the ROC curve), has been widely studied in recent years. …
This work analyzes two methods for combining multiple binary labels in bipartite ranking.
problem Combining multiple binary labels for optimal bipartite ranking.
method Loss aggregation vs. label aggregation approaches.
result Label aggregation is preferable to loss aggregation due to label dictatorship issues.
Recent years have witnessed a widespread increase of interest in network representation learning (NRL). By far most research efforts have focused on NRL for homogeneous networks like social networks where vertices are of the same type, or heterogeneous networks like knowledge graphs where vertices (and/or edges) are of…