Flip dynamics on perfect matchings beyond bipartite and planar graphs [PDF]
Vladimir Bošković
openalex +1 more source
It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar +2 more
wiley +1 more source
Alternative Entropy Bounds for Perfect Matchings in Bipartite Graphs [PDF]
Yusong Du, Boqing Xue
openalex +1 more source
Comparative Analysis of Model‐Agnostic Explanation Methods in Materials Science
To address the critical lack of explainable artificial intelligence (XAI) benchmarks in materials science, we present a quantitative and qualitative analysis of six XAI methods applied to molecular fingerprints. Our results reveal significant discrepancies in feature importance rankings, demonstrating that the chosen explanation approach introduces ...
Anna Przybyłowska +7 more
wiley +1 more source
Simplex polynomial in complex networks and its applications to compute the Euler characteristic. [PDF]
Wang Z, Fu X, Deng B, Chen Y, Zhao H.
europepmc +1 more source
On perfect matchings, edge-colourings and eigenvalues of cubic graphs [PDF]
Willem H. Haemers
openalex +1 more source
Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source
Predictive analytics for supply chain resilience in urban infrastructure networks using graph convolutional networks. [PDF]
Liu Y, Hu R, Zhang W, Wu Q.
europepmc +1 more source
A Polynomial-Time Algorithm for Coloring Perfect Graphs Based on Walk Counting [PDF]
Amir Ali Ahmadi +2 more
openalex +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source

