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Found 16 papers, 8 papers with code
Autonomous microARPES
Angle-resolved photoemission spectroscopy (ARPES) is a technique used to map the occupied electronic structure of solids.
EUGENE: Explainable Unsupervised Approximation of Graph Edit Distance
The need to identify graphs having small structural distance from a query arises in biology, chemistry, recommender systems, and social network analysis.
Data-driven prediction of tool wear using Bayesian-regularized artificial neural networks
The prediction of tool wear helps minimize costs and enhance product quality in manufacturing.
MCWDST: a Minimum-Cost Weighted Directed Spanning Tree Algorithm for Real-Time Fake News Mitigation in Social Media
The widespread availability of internet access and handheld devices confers to social media a power similar to the one newspapers used to have.
DANES: Deep Neural Network Ensemble Architecture for Social and Textual Context-aware Fake News Detection
The growing popularity of social media platforms has simplified the creation and distribution of news articles but also creates a conduit for spreading fake news.
Maximizing the Probability of Fixation in the Positional Voter Model
The Voter model is a well-studied stochastic process that models the invasion of a novel trait $A$ (e. g., a new opinion, social meme, genetic mutation, magnetic spin) in a network of individuals (agents, people, genes, particles) carrying an existing resident trait $B$.
Invasion Dynamics in the Biased Voter Process
We show that the problem is NP-hard for both $r>1$ and $r<1$, while the latter case is also inapproximable within any multiplicative factor.
Atrapos: Real-time Evaluation of Metapath Query Workloads
In this paper, we present ATRAPOS, a new approach for the real-time evaluation of metapath query workloads that leverages a combination of efficient sparse matrix multiplication and intermediate result caching.
GRASP: Graph Alignment through Spectral Signatures
In this paper, we transfer the shape-analysis concept of functional maps from the continuous to the discrete case, and treat the graph alignment problem as a special case of the problem of finding a mapping between functions on graphs.
FREDE: Anytime Graph Embeddings
Low-dimensional representations, or embeddings, of a graph's nodes facilitate several practical data science and data engineering tasks.
Equitable Stable Matchings in Quadratic Time
Can a stable matching that achieves high equity among the two sides of a market be reached in quadratic time?
The Shape of Data: Intrinsic Distance for Data Distributions
The ability to represent and compare machine learning models is crucial in order to quantify subtle model changes, evaluate generative models, and gather insights on neural network architectures.
SGR: Self-Supervised Spectral Graph Representation Learning
Representing a graph as a vector is a challenging task; ideally, the representation should be easily computable and conducive to efficient comparisons among graphs, tailored to the particular data and analytical task at hand.
NetLSD: Hearing the Shape of a Graph
However, it is a hard task in terms of the expressiveness of the employed similarity measure and the efficiency of its computation.
Social and Information Networks
VERSE: Versatile Graph Embeddings from Similarity Measures
Embedding a web-scale information network into a low-dimensional vector space facilitates tasks such as link prediction, classification, and visualization.
Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores
Stochastic cracking also uses each query as a hint on how to reorganize data, but not blindly so; it gains resilience and avoids performance bottlenecks by deliberately applying certain arbitrary choices in its decision-making.
