Mikko Koivisto
Impact in
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- Birth, Development, and Health
- Infant Development and Preterm Care
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- Advanced Graph Theory Research
- Complexity and Algorithms in Graphs
Papers in
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- Neonatal Health and Biochemistry 10
Mikko Koivisto
111 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 151
- Pediatrics, Perinatology and Child Health 583
- Computational Theory and Mathematics 386
- Discrete Mathematics and Combinatorics 73
- Endocrine and Autonomic Systems 126
- Pulmonary and Respiratory Medicine 524
Countries citing papers authored by Mikko Koivisto
This map shows the geographic impact of Mikko Koivisto's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mikko Koivisto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikko Koivisto more than expected).
Fields of papers citing papers by Mikko Koivisto
This network shows the impact of papers produced by Mikko Koivisto. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mikko Koivisto. The network helps show where Mikko Koivisto may publish in the future.
Co-authors
The 25 scholars most cited alongside Mikko Koivisto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Layering-MCMC for Structure Learning in Bayesian Networks. | 2020 | 0 |
| 2 | On Structure Priors for Learning Bayesian Networks | 2019 | 2 |
| 3 | Exact Sampling of Directed Acyclic Graphs from Modular Distributions | 2019 | 1 |
| 4 | Finding Optimal Bayesian Networks with Local Structure. | 2018 | 3 |
| 5 | AS-ASL: Algorithm Selection with Auto-sklearn | 2017 | 4 |
| 6 | Structure discovery in Bayesian networks by sampling partial orders | 2016 | 14 |
| 7 | Counting linear extensions of sparse posets | 2016 | 9 |
| 8 | Pruning rules for learning parsimonious context trees | 2016 | 3 |
| 9 | Dealing with small data: On the generalization of context trees | 2015 | 5 |
| 10 | Averaging of decomposable graphs by dynamic programming and sampling | 2015 | 3 |
| 11 | Finding optimal Bayesian networks using precedence constraints | 2013 | 11 |
| 12 | Treedy: a heuristic for counting and sampling subsets | 2013 | 1 |
| 13 | Annealed importance sampling for structure learning in Bayesian networks | 2013 | 13 |
| 14 | 2012 | 17 | |
| 15 | 2011 | 7 | |
| 16 | Bayesian structure discovery in Bayesian networks with less space | 2010 | 4 |
| 17 | Exact Bayesian Structure Discovery in Bayesian Networks | 2004 | 213 |
| 18 | 2004 | 5 | |
| 19 | 2001 | 1 | |
| 20 | Umbilical cord and neonatal cortisol levels. Effect of gestational and neonatal factors. | 1978 | 34 |
About Mikko Koivisto
Mikko Koivisto is a scholar working on Discrete Mathematics and Combinatorics, Pediatrics, Perinatology and Child Health, Statistics and Probability, Artificial Intelligence and Computational Theory and Mathematics, having authored 117 papers that have together received 2.3k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (26 papers), Neonatal Respiratory Health Research (16 papers), Advanced Graph Theory Research (12 papers), Neonatal Health and Biochemistry (10 papers), Bayesian Methods and Mixture Models (10 papers), Machine Learning and Algorithms (9 papers), Congenital Diaphragmatic Hernia Studies (8 papers) and Data Management and Algorithms (8 papers). The work is most often cited by research in Pediatrics, Perinatology and Child Health (583 citations), Computational Theory and Mathematics (386 citations), Discrete Mathematics and Combinatorics (73 citations), Endocrine and Autonomic Systems (126 citations) and Pulmonary and Respiratory Medicine (524 citations). Mikko Koivisto has collaborated with scholars based in Finland, Sweden and Denmark. Frequent co-authors include Thore Husfeldt, Andreas Björklund, Petteri Kaski, Antti Kauppila, M. Anneli Kari, Pentti Jouppila, Riikka Ikonen, R. Vihko, Olavi Ylikorkala and Juha S. Tapanainen. Their work appears in journals such as Acta Paediatrica, European Psychiatry, Neonatology, Acta Radiologica and Obstetrical & Gynecological Survey.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.