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Bruce Vanstone
- ESANN 2010 - Financial time series forecasting with machine learning techniques: a survey [Details]
- ESANN 2005 - clustering using a random walk based distance measure [Details]
- ESANN 2021 - Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data [Details]
- ESANN 2022 - Contrasting Explanation of Concept Drift [Details]
- ESANN 2022 - Federated learning vector quantization for dealing with drift between nodes [Details]
- ESANN 2022 - From hyperspectral to multispectral sensing – from simulation to reality: A comprehensive approach for calibration model transfer [Details]
- ESANN 2023 - Robust Feature Selection and Robust Training to Cope with Hyperspectral Sensor Shifts [Details]
- ESANN 2024 - Causes of Rejects in Prototype-based Classification Aleatoric vs. Epistemic Uncertainty [Details]
- ESANN 2024 - On the Fine Structure of Drifting Features [Details]
- ESANN 2024 - Self-Supervised Learning from Incrementally Drifting Data Streams [Details]
- ESANN 2024 - Self-Supervised Learning from Incrementally Drifting Data Streams [Details]
- ESANN 1993 - An intuitive characterization for the reference vectors of a Kohonen map [Details]
- ESANN 1994 - Decoding functions for Kohonen maps [Details]
- ESANN 1996 - Error rate estimation via cross-validation and learning curve theory [Details]
- ESANN 2019 - time series modelling of market price in real-time bidding [Details]
- ESANN 1998 - Recurrent SOM with local linear models in time series prediction [Details]
- ESANN 2000 - Analytical comparison of the Temporal Kohonen Map and the Recurrent Self Organizing Map [Details]
- ESANN 2023 - An Alternating Minimization Algorithm with Trajectory for Direct Exoplanet Detection [Details]
- ESANN 2020 - Unsupervised Latent Space Translation Network [Details]
- ESANN 2015 - Revisiting ant colony algorithms to seismic faults detection [Details]
- ESANN 2023 - Real-time Detection of Evoked Potentials by Deep Learning: a Case Study [Details]
- ESANN 1995 - XOR and backpropagation learning: in and out of the chaos? [Details]
- ESANN 1997 - An algebra for recognition of spatio-temporal forms [Details]
- ESANN 2003 - A Spiking Machine for Human-Computer Interactions (Design methodology) [Details]
- ESANN 2002 - A data vizualisation method for investigating the reliability of a high-dimensional low-back-pain MLP network [Details]
- No papers found
- ESANN 1995 - A deterministic method for establishing the initial conditions in the RCE algorithm [Details]
- ESANN 2010 - Adaptive matrix distances aiming at optimum regression subspaces [Details]
- ESANN 2023 - Evaluating Curriculum Learning Strategies for Pancreatic Cancer Prediction [Details]
- ESANN 2020 - Machine learning framework for control in classical and quantum domains [Details]
- ESANN 2007 - Kernel-based online machine learning and support vector reduction [Details]
- ESANN 2024 - Interpreting Hybrid AI through Autodecoded Latent Space Entities [Details]
- ESANN 2024 - On the Stability of Neural Segmentation in Radiology [Details]
- ESANN 2014 - Finding Originally Mislabels with MD-ELM [Details]
- ESANN 2019 - Weightless neural systems for deforestation surveillance and image-based navigation of UAVs in the Amazon forest [Details]
- ESANN 2018 - Multi-omics data integration using cross-modal neural networks [Details]
- ESANN 2004 - Data Mining Techniques on the Evaluation of Wireless Churn [Details]
- ESANN 2005 - Functional topographic mapping for robust handling of outliers in brain tumour data [Details]
- ESANN 2005 - Handling outliers and missing data in brain tumour clinical assessment using t-GTM [Details]
- ESANN 2006 - Learning what is important: feature selection and rule extraction in a virtual course [Details]
- ESANN 2007 - Identification of churn routes in the Brazilian telecommunications market [Details]
- ESANN 2008 - DSS-oriented exploration of a multi-centre magnetic resonance spectroscopy brain tumour dataset through visualization [Details]
- ESANN 2008 - Machine learning in cancer research: implications for personalised medicine [Details]
- ESANN 2010 - Computational Intelligence in biomedicine: Some contributions [Details]
- ESANN 2010 - Kernel generative topographic mapping [Details]
- ESANN 2010 - Segmentation of EMG time series using a variational Bayesian approach for the robust estimation of cortical silent periods [Details]
- ESANN 2010 - Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis [Details]
- ESANN 2011 - A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences [Details]
- ESANN 2011 - Seeing is believing: The importance of visualization in real-world machine learning applications [Details]
- ESANN 2012 - Cartogram representation of the batch-SOM magnification factor [Details]
- ESANN 2012 - Making machine learning models interpretable [Details]
- ESANN 2013 - A quotient basis kernel for the prediction of mortality in severe sepsis patients [Details]
- ESANN 2013 - Robust cartogram visualization of outliers in manifold learning [Details]
- ESANN 2013 - Visualizing pay-per-view television customers churn using cartograms and flow maps [Details]
- ESANN 2016 - A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases [Details]
- ESANN 2016 - Bayesian semi non-negative matrix factorisation [Details]
- ESANN 2016 - Physics and Machine Learning: Emerging Paradigms [Details]
- ESANN 2018 - Bioinformatics and medicine in the era of deep learning [Details]
- ESANN 2019 - Societal Issues in Machine Learning: When Learning from Data is Not Enough [Details]
- ESANN 2021 - The Coming of Age of Interpretable and Explainable Machine Learning Models [Details]
- ESANN 2014 - Misclassification of class C G-protein-coupled receptors as a label noise problem [Details]
- ESANN 1998 - Parsimonious learning feed-forward control [Details]