| 2021 | IJCNN | Artificial Neural Networks as Feature Extractors in Continuous Evolutionary Optimization. | Stephen Friess, Peter Tio, Zhao Xu, Stefan Menzel, Bernhard Sendhoff, Xin Yao |
| 2021 | IJCNN | Interpreting Node Embedding with Text-labeled Graphs. | Giuseppe Serra, Zhao Xu, Mathias Niepert, Carolin Lawrence, Peter Tio, Xin Yao |
| 2020 | CEC | Representing Experience in Continuous Evolutionary optimisation through Problem-tailored Search Operators. | Stephen Friess, Peter Tio, Stefan Menzel, Bernhard Sendhoff, Xin Yao |
| 2020 | ESANN | ASAP - A Sub-sampling Approach for Preserving Topological Structures. | Abolfazl Taghribi, Kerstin Bunte, Michele Mastropietro, Sven De Rijcke, Peter Tio |
| 2020 | IJCNN | Visualisation and knowledge discovery from interpretable models. | Sreejita Ghosh, Peter Tio, Kerstin Bunte |
| 2020 | PPSN | Improving Sampling in Evolution Strategies Through Mixture-Based Distributions Built from Past Problem Instances. | Stephen Friess, Peter Tio, Stefan Menzel, Bernhard Sendhoff, Xin Yao |
| 2019 | AAAI | Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets. | Mara Prez-Ortiz, Peter Tio, Rafal Mantiuk, Csar Hervs-Martnez |
| 2019 | ESANN | Feature relevance bounds for ordinal regression. | Lukas Pfannschmidt, Jonathan Jakob, Michael Biehl, Peter Tio, Barbara Hammer |
| 2019 | GECCO | Extended stochastic derivative-free optimization on riemannian manifolds. | Robert Simon Fong, Peter Tio |
| 2018 | ESANN | Machine learning and data analysis in astroinformatics. | Michael Biehl, Kerstin Bunte, Giuseppe Longo, Peter Tio |
| 2018 | ESANN | Randomized Recurrent Neural Networks. | Claudio Gallicchio, Alessio Micheli, Peter Tio |
| 2018 | IJCNN | A mixture of experts model for predicting persistent weather patterns. | M. Prez-Ortiz, Pedro Antonio Gutirrez, Peter Tio, Carlos Casanova-Mateo, Sancho Salcedo-Sanz |
| 2018 | SSPR | Sparsification of Indefinite Learning Models. | Frank-Michael Schleif, Christoph Raab, Peter Tio |
| 2017 | ESANN | Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders. | Sreejita Ghosh, Elizabeth Sarah Baranowski, Rick van Veen, Gert-Jan de Vries, Michael Biehl, Wiebke Arlt, Peter Tio, Kerstin Bunte |
| 2017 | ESANN | Fisher memory of linear Wigner echo state networks. | Peter Tio |
| 2017 | IJCNN | Linear dynamical based models for sequential domains. | Luca Pasa, Alessandro Sperduti, Peter Tio |
| 2017 | IJCNN | Classification of sparsely and irregularly sampled time series: A learning in model space approach. | Yuan Shen, Peter Tio, Krasimira Tsaneva-Atanasova |
| 2017 | IJCNN | Probabilistic matching: Causal inference under measurement errors. | Fani Tsapeli, Peter Tio, Mirco Musolesi |
| 2017 | ICWS | Self-Awareness for Dynamic Knowledge Management in Self-Adaptive Volunteer Services. | Abdessalam Elhabbash, Rami Bahsoon, Peter Tio |
| 2016 | ESANN | Learning in indefinite proximity spaces - recent trends. | Frank-Michael Schleif, Peter Tio, Yingyu Liang |
| 2016 | IDEAL | Probabilistic Modelling for Delay Estimation in Gravitationally Lensed Photon Streams. | Sultanah Al Otaibi, Peter Tio, Somak Raychaudhury |
| 2015 | ESANN | Autoencoding time series for visualisation. | Nikolaos Gianniotis, Sven Dennis Kgler, Peter Tio, Kai Polsterer, Ranjeev Misra |
| 2015 | ESANN | Probabilistic Classification Vector Machine at large scale. | Frank-Michael Schleif, Andrej Gisbrecht, Peter Tio |
| 2015 | ICONIP | Automated Detection of Galaxy Groups Through Probabilistic Hough Transform. | Rafee T. Ibrahem, Peter Tio, Richard J. Pearson, Trevor J. Ponman, Arif Babul |
| 2015 | IJCAI | Model Metric Co-Learning for Time Series Classification. | Huanhuan Chen, Fengzhen Tang, Peter Tio, Anthony G. Cohn, Xin Yao |
| 2015 | IJCNN | Incremental probabilistic classification vector machine with linear costs. | Frank-Michael Schleif, H. Chen, Peter Tio |
| 2015 | ICWS | Self-Adaptive Volunteered Services Composition through Stimulus- and Time-Awareness. | Abdessalam Elhabbash, Rami Bahsoon, Peter Tio, Peter R. Lewis |
| 2014 | ESANN | Recent trends in learning of structured and non-standard data. | Frank-Michael Schleif, Peter Tio, Thomas Villmann |
| 2014 | ESANN | Support Vector Ordinal Regression using Privileged Information. | Fengzhen Tang, Peter Tio, Pedro Antonio Gutirrez, Huanhuan Chen |
| 2014 | HPCC | Towards Self-Aware Service Composition. | Abdessalam Elhabbash, Rami Bahsoon, Peter Tio |
| 2014 | IJCNN | Learning the deterministically constructed Echo State Networks. | Fengzhen Tang, Peter Tio, Huanhuan Chen |
| 2014 | UCC | A Utility Model for Volunteered Service Composition. | Abdessalam Elhabbash, Rami Bahsoon, Peter Tio, Peter R. Lewis |
| 2013 | CIDM | A principled approach to mining from noisy logs using Heuristics Miner. | Phil Weber, Behzad Bordbar, Peter Tio |
| 2013 | IJCNN | Ordinal-based metric learning for learning using privileged information. | Shereen Fouad, Peter Tio |
| 2013 | IJCNN | Concept drift detection for online class imbalance learning. | Shuo Wang, Leandro L. Minku, Davide Ghezzi, Daniele Caltabiano, Peter Tio, Xin Yao |
| 2013 | KDD | Model-based kernel for efficient time series analysis. | Huanhuan Chen, Fengzhen Tang, Peter Tio, Xin Yao |
| 2013 | MICCAI | A Spatial Mixture Approach to Inferring Sub-ROI Spatio-temporal Patterns from Rapid Event-Related fMRI Data. | Yuan Shen, Stephen D. Mayhew, Zoe Kourtzi, Peter Tio |
| 2012 | ESANN | Theory of Input Driven Dynamical Systems. | Manjunath Gandhi, Peter Tio, Herbert Jaeger |
| 2012 | ESANN | Short Term Memory Quantifications in Input-Driven Linear Dynamical Systems. | Peter Tio, Ali Rodan |
| 2012 | ESANN | Process Mining in Non-Stationary Environments. | Phil Weber, Peter Tio, Behzad Bordbar |
| 2012 | ICANN | Learning Using Privileged Information in Prototype Based Models. | Shereen Fouad, Peter Tio, Somak Raychaudhury, Petra Schneider |
| 2012 | IDEAL | Prototype Based Modelling for Ordinal Classification. | Shereen Fouad, Peter Tio |
| 2011 | ESANN | Negatively Correlated Echo State Networks. | Ali Rodan, Peter Tio |
| 2011 | ICANN | Time-Dependent Series Variance Estimation via Recurrent Neural Networks. | Nikolay I. Nikolaev, Peter Tio, Evgueni N. Smirnov |
| 2011 | IDEAL | A Principled Approach to the Analysis of Process Mining Algorithms. | Phil Weber, Behzad Bordbar, Peter Tio |
| 2011 | ISNN | One-Shot Learning of Poisson Distributions in Serial Analysis of Gene Expression. | Peter Tio |
| 2010 | ECMS | On Reliability Of Simulations Of Complex Co-Evolutionary Processes. | Peter Tio, Siang Yew Chong, Xin Yao |
| 2010 | ICANN | Multilinear Decomposition and Topographic Mapping of Binary Tensors. | Jakub Mazgut, Peter Tio, Mikael Bodn, Hong Yan |
| 2010 | IDEAL | Simple Deterministically Constructed Recurrent Neural Networks. | Ali Rodan, Peter Tio |
| 2009 | ICANN | Topographic Mapping of Astronomical Light Curves via a Physically Inspired Probabilistic Model. | Nikolaos Gianniotis, Peter Tio, Steve Spreckley, Somak Raychaudhury |
| 2009 | IJCNN | Fast parzen window density estimator. | Xiaoxia Wang, Peter Tio, Mark A. Fardal, Somak Raychaudhury, Arif Babul |
| 2008 | ICANN | Predictive Modeling with Echo State Networks. | Michal Cernansk, Peter Tio |
| 2007 | ESANN | Visualisation of tree-structured data through generative probabilistic modelling. | Nikolaos Gianniotis, Peter Tio |
| 2007 | ICANN | Comparison of Echo State Networks with Simple Recurrent Networks and Variable-Length Markov Models on Symbolic Sequences. | Michal Cernansk, Peter Tio |
| 2007 | ICONIP | Bifurcations of Renormalization Dynamics in Self-organizing Neural Networks. | Peter Tio |
| 2007 | IJCAI | Metric Properties of Structured Data Visualizations through Generative Probabilistic Modeling. | Peter Tio, Nikolaos Gianniotis |
| 2006 | ICDM | A Probabilistic Ensemble Pruning Algorithm. | Huanhuan Chen, Peter Tio, Xin Yao |
| 2006 | PPSN | Critical Temperatures for Intermittent Search in Self-Organizing Neural Networks. | Peter Tio |
| 2005 | ICNC | On Non-markovian Topographic Organization of Receptive Fields in Recursive Self-organizing Map. | Peter Tio, Igor Farkas |
| 2005 | ICNC | Learning Beyond Finite Memory in Recurrent Networks of Spiking Neurons. | Peter Tio, Ashley J. S. Mills |
| 2005 | IDEAL | Recursive Self-organizing Map as a Contractive Iterative Function System. | Peter Tio, Igor Farkas, Jort van Mourik |
| 2004 | KDD | A generative probabilistic approach to visualizing sets of symbolic sequences. | Peter Tio, Ata Kabn, Yi Sun |
| 2004 | PPSN | Evaluation of Adaptive Nature Inspired Task Allocation Against Alternate Decentralised Multiagent Strategies. | Richard Price, Peter Tio |
| 2002 | ICANN | Architectural Bias in Recurrent Neural Networks - Fractal Analysis. | Peter Tio, Barbara Hammer |
| 2002 | IDEAL | A General Framework for a Principled Hierarchical Visualization of Multivariate Data. | Ata Kabn, Peter Tio, Mark A. Girolami |
| 2001 | ICANN | Using Directional Curvatures to Visualize Folding Patterns of the GTM Projection Manifolds. | Peter Tio, Ian T. Nabney, Yi Sun |
| 2000 | IJCNN | Building Predictive Models on Complex Symbolic Sequences with a Second-Order Recurrent BCM Network with Lateral Inhibition. | Peter Tio, Michal Stanck, Lubica Benuskov |
| 1997 | KES | Extracting stochastic machines from recurrent neural networks trained on complex symbolic sequences. | Peter Tio, V. Vojtek |