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Peter Sykacek
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2020 – today
- 2020
- [j11]Peter Sykacek
:
Biased Against Race or Age? IEEE Softw. 37(4): 22 (2020)
2010 – 2019
- 2012
- [j10]Peter Sykacek:
Bayesian assignment of gene ontology terms to gene expression experiments. Bioinform. 28(18): 603-610 (2012) - 2011
- [j9]Alexandra Posekany, K. Felsenstein, Peter Sykacek:
Biological assessment of robust noise models in microarray data analysis. Bioinform. 27(6): 807-814 (2011) - [j8]Peter Sykacek, David P. Kreil, Lisa A. Meadows, Richard P. Auburn, Bettina Fischer, Steven Russell
, Gos Micklem
:
The impact of quantitative optimization of hybridization conditions on gene expression analysis. BMC Bioinform. 12: 73 (2011) - [j7]Pawel P. Labaj, Peter Sykacek
, David P. Kreil:
An analysis of single amino acid repeats as use case for application specific background models. BMC Bioinform. 12: 173 (2011)
2000 – 2009
- 2007
- [j6]Peter Sykacek, R. Clarkson, Cristin G. Print
, R. A. Furlong, Gos Micklem
:
Bayesian modelling of shared gene function. Bioinform. 23(15): 1936-1944 (2007) - 2005
- [j5]Peter Sykacek, R. A. Furlong, Gos Micklem
:
A friendly statistics package for microarray analysis. Bioinform. 21(21): 4069-4070 (2005) - 2004
- [j4]Peter Sykacek, Stephen J. Roberts, Maria Stokes
:
Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation. IEEE Trans. Biomed. Eng. 51(5): 719-727 (2004) - 2003
- [j3]S. N. Mukherjee, Stephen J. Roberts, Peter Sykacek, Sarah J. Gurr:
Gene ranking using bootstrapped P-values. SIGKDD Explor. 5(2): 16-22 (2003) - [c11]Iead Rezek, Stephen J. Roberts, Peter Sykacek:
Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic Signals. AISTATS 2003: 233-239 - 2002
- [j2]Arthur Flexer
, Georg Dorffner
, Peter Sykacek, Iead Rezek:
An Automatic, Continuous and Probabilistic Sleep Stager Based on a Hidden Markov Model. Appl. Artif. Intell. 16(3): 199-207 (2002) - [j1]Peter Sykacek, Georg Dorffner
, Peter Rappelsberger, Josef Zeitlhofer:
Improving Biosignal Processing through Modeling Uncertainty: Bayes vs. Non-Bayes in Sleep Staging. Appl. Artif. Intell. 16(5): 395-421 (2002) - [c10]Peter Sykacek, Stephen J. Roberts:
Adaptive Classification by Variational Kalman Filtering. NIPS 2002: 737-744 - 2001
- [c9]Peter Sykacek, Stephen J. Roberts, Iead Rezek, Arthur Flexer
, Georg Dorffner
:
A Probabilistic Approach to High-Resolution Sleep Analysis. ICANN 2001: 617-624 - [c8]Peter Sykacek, Stephen J. Roberts:
Bayesian time series classification. NIPS 2001: 937-944 - 2000
- [c7]Georg Dorffner, Peter Sykacek, Christian Schittenkopf:
Modelling Uncertainty in Biomedical Applications of Neural Networks. ANNIMAB 2000: 18-25 - [c6]Arthur Flexer
, Peter Sykacek, Georg Dorffner, Iead Rezek:
Using Hidden Markov Models to Build an Automatic, Continuous and Probabilistic Sleep Stager. IJCNN (3) 2000: 627-631
1990 – 1999
- 1999
- [c5]Peter Sykacek:
On Input Selection with Reversible Jump Markov Chain Monte Carlo Sampling. NIPS 1999: 638-644 - 1998
- [c4]Nello Cristianini, John Shawe-Taylor, Peter Sykacek:
Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space. ICML 1998: 109-117 - [c3]Peter Sykacek:
Outliers and Bayesian Inference. NC 1998: 973-978 - 1997
- [c2]Peter Sykacek:
Equivalent error bars for neural network classifiers trained by Bayesian inference. ESANN 1997 - [c1]Peter Sykacek, Georg Dorffner, Peter Rappelsberger, Josef Zeitlhofer:
Experiences with Bayesian Learning in a Real World Application. NIPS 1997: 964-970
Coauthor Index
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