Peter Sykacek

发表

Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic Signals

Stephen J. Roberts, Iead Rezek, Peter Sykacek, 2003, AISTATS.

An analysis of single amino acid repeats as use case for application specific background models

Peter Sykacek, Pawel P. Labaj, David P. Kreil, 2011, BMC Bioinformatics.

Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space

Nello Cristianini, John Shawe-Taylor, Peter Sykacek, 1998, ICML.

Bayes Consistent Classification of EEG Data by Approximate Marginalization

Stephen J. Roberts, Iead Rezek, Peter Sykacek, 2005 .

Outliers and Bayesian Inference

Peter Sykacek, P. Sykacek, 1998, NC.

Bayesian assignment of gene ontology terms to gene expression experiments

Peter Sykacek, P. Sykacek, 2012, Bioinform..

A friendly statistics package for microarray analysis

Gos Micklem, Peter Sykacek, R. A. Furlong, 2005, Bioinform..

Biased Against Race or Age?

Peter Sykacek, 2020, IEEE Softw..

The impact of quantitative optimization of hybridization conditions on gene expression analysis

Gos Micklem, Peter Sykacek, Steven Russell, 2011, BMC Bioinformatics.

Detection of the EEG Artifacts by the Means of the (Extended) Kalman Filter

Georg Dorffner, Peter Sykacek, P. Sykacek, 2001 .

Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation

Stephen J. Roberts, Peter Sykacek, Maria Stokes, 2004, IEEE Transactions on Biomedical Engineering.

Gene ranking using bootstrapped P-values

Stephen J. Roberts, Sarah J. Gurr, Peter Sykacek, 2003, SKDD.

Biological assessment of robust noise models in microarray data analysis

Peter Sykacek, K. Felsenstein, Alexandra Posekany, 2011, Bioinform..

Comparison of Unsupervised Learning Methods for Natural Image Processing

Cristina Olaverri-Monreal, Wilfried Wöber, Peter Sykacek, 2019, Biodiversity Information Science and Standards.

Adaptive BCI based on variational Bayes: an empirical evaluation

Stephen J. Roberts, Peter Sykacek, Maria Stokes, 2002 .

Equivalent error bars for neural network classifiers trained by Bayesian inference

Peter Sykacek, P. Sykacek, 1997, ESANN.

An automatic, continuous and probabilistic sleep stager based on a hidden markov model

Georg Dorffner, Arthur Flexer, Peter Sykacek, 2002, Appl. Artif. Intell..

Bayesian Inference for Reliable Biomedical Signal Processing

Peter Sykacek, 2000 .

Improving biosignal processing through modeling uncertainty: Bayes vs. non-bayes in sleep staging

Georg Dorffner, Peter Rappelsberger, Peter Sykacek, 2002, Appl. Artif. Intell..

Bayesian Modelling of Shared Gene Function

Gos Micklem, Peter Sykacek, Cristin G. Print, 2022 .

Adaptive Classification by Variational Kalman Filtering

Stephen J. Roberts, Peter Sykacek, S. Roberts, 2002, NIPS.

A Probabilistic Approach to High-Resolution Sleep Analysis

Stephen J. Roberts, Georg Dorffner, Arthur Flexer, 2001, ICANN.

Véronique Monnet, Jean-François Gibrat, Olivier David, 2014 .

Experiences with Bayesian Learning in a Real World Application

Georg Dorffner, Peter Rappelsberger, Peter Sykacek, 1997, NIPS.

Véronique Monnet, Jean-François Gibrat, Olivier David, 2014 .

Modelling Uncertainty in Biomedical Applications of Neural Networks

Georg Dorffner, Peter Sykacek, Christian Schittenkopf, 2000, ANNIMAB.

On Input Selection with Reversible Jump Markov Chain Monte Carlo Sampling

Peter Sykacek, P. Sykacek, 1999, NIPS.

Using hidden Markov models to build an automatic, continuous and probabilistic sleep stager

Georg Dorffner, Arthur Flexer, Iead Rezek, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Bayesian time series classification

Stephen J. Roberts, Peter Sykacek, 2001, NIPS.

Coupled hidden Markov models for biosignal interaction modelling

Stephen J. Roberts, Peter Sykacek, L. Rezek, 2000 .

Root traits of European Vicia faba cultivars-Using machine learning to explore adaptations to agroclimatic conditions.

Peter Sykacek, Gernot Bodner, Boris Rewald, 2017, Plant, cell & environment.

RNA Interference in Ageing Research – A Mini-Review

Peter Sykacek, David P. Kreil, Brian Godsey, 2010, Gerontology.

Detecting and correcting systematic variation in large-scale RNA sequencing data

Wei Shi, Leming Shi, Jean Thierry-Mieg, 2014, Nature Biotechnology.