3 papers
math.ST2026
Robust estimation of a Markov chain transition matrix from multiple sample paths
Lasse Leskelä, Maximilien Dreveton
Markov chains are fundamental models for stochastic dynamics, with applications in a wide range of areas such as population dynamics, queueing systems, reinforcement learning, and…
math.CO2024
Connectivity of random hypergraphs with a given hyperedge size distribution
Elmer Bergman, Lasse Leskelä
This article discusses random hypergraphs with varying hyperedge sizes, admitting large hyperedges with size tending to infinity, and heavy-tailed limiting hyperedge size distribut…
physics.data-an2024
Distinguishing subsampled power laws from other heavy-tailed distributions
Silja Sormunen, Lasse Leskelä, Jari Saramäki
Distinguishing power-law distributions from other heavy-tailed distributions is challenging, and this task is often further complicated by subsampling effects. In this work, we eva…