16 citations · 38 across the 7 of their papers we have counts for
10 papers
odeN: Simultaneous Approximation of Multiple Motif Counts in Large Temporal Networks
Ilie Sarpe, Fabio Vandin
Counting the number of occurrences of small connected subgraphs, called temporal motifs, has become a fundamental primitive for the analysis of temporal networks, whose edges are a…
PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts
Ilie Sarpe, Fabio Vandin
The identification and counting of small graph patterns, called network motifs, is a fundamental primitive in the analysis of networks, with application in various domains, from so…
SPRISS: Approximating Frequent -mers by Sampling Reads, and Applications
Diego Santoro, Leonardo Pellegrina, Fabio Vandin
The extraction of -mers is a fundamental component in many complex analyses of large next-generation sequencing datasets, including reads classification in genomics and the char…
A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings
Davide Buffelli, Fabio Vandin
Graph Neural Networks (GNNs) are a framework for graph representation learning, where a model learns to generate low dimensional node embeddings that encapsulate structural and fea…
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining
Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin +1
We present MCRapper, an algorithm for efficient computation of Monte-Carlo Empirical Rademacher Averages (MCERA) for families of functions exhibiting poset (e.g., lattice) structur…
Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation
Davide Buffelli, Fabio Vandin
Sensor-based human activity recognition (HAR) requires to predict the action of a person based on sensor-generated time series data. HAR has attracted major interest in the past fe…