| * | 2008 |
|---|
| 8 | EE | Pedro C. Pinto,
Andreas Nägele,
Mathäus Dejori,
Thomas A. Runkler,
João Miguel da Costa Sousa:
Learning of Bayesian networks by a local discovery ant colony algorithm.
IEEE Congress on Evolutionary Computation 2008: 2741-2748 |
| 7 | EE | Fabian Mörchen,
Mathäus Dejori,
Dmitriy Fradkin,
Julien Etienne,
Bernd Wachmann,
Markus Bundschus:
Anticipating annotations and emerging trends in biomedical literature.
KDD 2008: 954-962 |
| 6 | EE | Markus Bundschus,
Mathäus Dejori,
Martin Stetter,
Volker Tresp,
Hans-Peter Kriegel:
Extraction of semantic biomedical relations from text using conditional random fields.
BMC Bioinformatics 9: (2008) |
| 2007 |
|---|
| 5 | EE | Andreas Nägele,
Mathäus Dejori,
Martin Stetter:
Bayesian Substructure Learning - Approximate Learning of Very Large Network Structures.
ECML 2007: 238-249 |
| 4 | EE | Anton Schwaighofer,
Mathäus Dejori,
Volker Tresp,
Martin Stetter:
Structure Learning with Nonparametric Decomposable Models.
ICANN (1) 2007: 119-128 |
| 2004 |
|---|
| 3 | EE | Mathäus Dejori,
Martin Stetter:
Identifying Interventional and Pathogenic Mechanisms by Generative Inverse Modeling of Gene Expression Profiles.
Journal of Computational Biology 11(6): 1135-1148 (2004) |
| 2003 |
|---|
| 2 | | Mathäus Dejori,
Martin Stetter:
Bayesian Inference of Genetic Networks from Gene-Expression-Data: Convergence and Reliability.
IC-AI 2003: 323-327 |
| 1 | EE | Martin Stetter,
Gustavo Deco,
Mathäus Dejori:
Large-Scale Computational Modeling of Genetic Regulatory Networks.
Artif. Intell. Rev. 20(1-2): 75-93 (2003) |
