2003 |
12 | EE | S. N. Mukherjee,
Stephen J. Roberts,
Peter Sykacek,
Sarah J. Gurr:
Gene ranking using bootstrapped P-values.
SIGKDD Explorations 5(2): 16-22 (2003) |
2002 |
11 | EE | Peter Sykacek,
Stephen J. Roberts:
Adaptive Classification by Variational Kalman Filtering.
NIPS 2002: 737-744 |
10 | EE | Arthur Flexer,
Georg Dorffner,
Peter Sykacek,
Iead Rezek:
An Automatic, Continuous and Probabilistic Sleep Stager Based on a Hidden Markov Model.
Applied Artificial Intelligence 16(3): 199-207 (2002) |
9 | EE | Peter Sykacek,
Georg Dorffner,
Peter Rappelsberger,
Josef Zeitlhofer:
Improving Biosignal Processing through Modeling Uncertainty: Bayes vs. Non-Bayes in Sleep Staging.
Applied Artificial Intelligence 16(5): 395-421 (2002) |
2001 |
8 | EE | Peter Sykacek,
Stephen J. Roberts,
Iead Rezek,
Arthur Flexer,
Georg Dorffner:
A Probabilistic Approach to High-Resolution Sleep Analysis.
ICANN 2001: 617-624 |
7 | EE | Peter Sykacek,
Stephen J. Roberts:
Bayesian time series classification.
NIPS 2001: 937-944 |
2000 |
6 | EE | 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 |
1999 |
5 | EE | Peter Sykacek:
On Input Selection with Reversible Jump Markov Chain Monte Carlo Sampling.
NIPS 1999: 638-644 |
1998 |
4 | | Nello Cristianini,
John Shawe-Taylor,
Peter Sykacek:
Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space.
ICML 1998: 109-117 |
3 | | Peter Sykacek:
Outliers and Bayesian Inference.
NC 1998: 973-978 |
1997 |
2 | | Peter Sykacek:
Equivalent error bars for neural network classifiers trained by Bayesian inference.
ESANN 1997 |
1 | | Peter Sykacek,
Georg Dorffner,
Peter Rappelsberger,
Josef Zeitlhofer:
Experiences with Bayesian Learning in a Real World Application.
NIPS 1997 |