Results 51 to 60 of about 8,099 (222)
Hypergraph partitioning using tensor eigenvalue decomposition.
Hypergraphs have gained increasing attention in the machine learning community lately due to their superiority over graphs in capturing super-dyadic interactions among entities.
Deepak Maurya, Balaraman Ravindran
doaj +1 more source
Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen +3 more
wiley +1 more source
Chain and threshold hypergraphs
Threshold graphs and chain graphs are the graphs with maximum spectral radius among the family of all connected graphs and connected bipartite graphs, respectively.
Shashwath S. Shetty, Arathi Bhat K
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This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
07281 Open Problems – Structure Theory and FPT Algorithmcs for Graphs, Digraphs and Hypergraphs
The following is a list of the problems presented on Monday, July 9, 2007 at the open-problem session of the Seminar on Structure Theory and FPT Algorithmics for Graphs, Digraphs and Hypergraphs, held at Schloss Dagstuhl in Wadern ...
Stege, Ulrike +3 more
core +1 more source
Complement Reducible Uniform Hypergraphs
We investigate a generalization of complement reducible graphs, called co-graphs, for r-uniform hypergraphs. The operations of r-co-hypergraphs are the disjoint union of two given r-co-hypergraphs and the join operation, which inserts all hyperedges of ...
Frank Gurski, Jochen Rethmann
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Saliency Detection Method Using Hypergraphs on Adaptive Multiscales
Saliency detection plays an important role in the fields of image processing and computer vision. We present an improved saliency detection method by means of hypergraphs on adaptive multi-scales (HAM).
Feilin Han, Aili Han, Jing Hao
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On Tight Tree‐Complete Hypergraph Ramsey Numbers
ABSTRACT Chvátal showed that for any tree T $T$ with k $k$ edges, the Ramsey number R ( T , n ) = k ( n − 1 ) + 1 $R(T,n)=k(n-1)+1$. For r = 3 $r=3$ or 4, we show that, if T $T$ is an r $r$‐uniform nontrivial tight tree, then the hypergraph Ramsey number R ( T , n ) = Θ ( n r − 1 ) $R(T,n)={\rm{\Theta }}({n}^{r-1})$.
Jiaxi Nie
wiley +1 more source
A lifting of graphs to 3-uniform hypergraphs, its generalization, and further investigation of hypergraph Ramsey numbers [PDF]
Ramsey theory has posed many interesting questions for graph theorists that have yet to besolved. Many different methods have been used to find Ramsey numbers, though very feware actually known.
NC DOCKS at Western Carolina University +1 more
core
Niche Hypergraphs of Products of Digraphs
If D = (V, A) is a digraph, its niche hypergraph Nℋ(D) = (V, ℰ) has the edge set ℰ={e⊆V||e|≥2∧∃ υ∈V:e=ND−(υ)∨e=ND+(υ)}{\cal E} = \{ {e \subseteq V| | e | \ge 2 \wedge \exists \, \upsilon \in V:e = N_D^ - ( \upsilon ) \vee e = N_D^ + ( \upsilon ...
Sonntag Martin, Teichert Hanns-Martin
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