Some Open Questions About the Anisotropic Random Walks

Between 2007 and 2018, we collaborated extensively with Pál Révész and Miklós Csörgő on many of the problems discussed in this paper. Over the past six years, we have continued to explore these issues, and here, we present some of the most intriguing open questions in these areas. This paper compiles key results from a dozen of our previous works, providing the necessary background to frame these compelling unresolved questions.

Authors

Institutions

Publication Details

Journal
Entropy
Published
2024-12-11
DOI
https://doi.org/10.3390/e26121082
Primary Topic
Markov Chains and Monte Carlo Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Some Open Questions About the Anisotropic Random Walks

Antónia Földes, Endre Csáki
Entropy
Markov Chains and Monte Carlo Methods
article

Some Open Questions About the Anisotropic Random Walks

Antónia Földes, Endre Csáki
article en

Abstract

Between 2007 and 2018, we collaborated extensively with Pál Révész and Miklós Csörgő on many of the problems discussed in this paper. Over the past six years, we have continued to explore these issues, and here, we present some of the most intriguing open questions in these areas. This paper compiles key results from a dozen of our previous works, providing the necessary background to frame these compelling unresolved questions.

EntropyVol. 26(12)
HUN-REN Alfréd Rényi Institute of Mathematics (HU), College of Staten Island (US), City University of New York (US)
Openalex Percentile: Top 77%
Markov Chains and Monte Carlo Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.