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Robin Tilman
- ESANN 2023 - Single-pass uncertainty estimation with layer ensembling for regression: application to proton therapy dose prediction for head and neck cancer [Details]
- ESANN 2019 - Learning multimodal fixed-point weights using gradient descent [Details]
- ESANN 2008 - Multi-class classification of ovarian tumors [Details]
- ESANN 2000 - Application of MLP and stochastic simulations for electricity load forecasting in Russia [Details]
- ESANN 2010 - Machine learning analysis and modeling of interest rate curves [Details]
- ESANN 2010 - Time series input selection using multiple kernel learning [Details]
- ESANN 2017 - Feature Extraction and Learning for RSSI based Indoor Device Localization [Details]
- ESANN 2023 - Introducing Convolutional Channel-wise Goodness in Forward-Forward Learning [Details]
- ESANN 2020 - ASAP - A Sub-sampling Approach for Preserving Topological Structures [Details]
- ESANN 2007 - Visualisation of tree-structured data through generative probabilistic modelling [Details]
- ESANN 2011 - Negatively Correlated Echo State Networks [Details]
- ESANN 2014 - Recent trends in learning of structured and non-standard data [Details]
- ESANN 2014 - Support Vector Ordinal Regression using Privileged Information [Details]
- ESANN 2015 - Autoencoding time series for visualisation [Details]
- ESANN 2015 - Probabilistic Classification Vector Machine at large scale [Details]
- ESANN 2016 - Learning in indefinite proximity spaces - recent trends [Details]
- ESANN 2017 - Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders [Details]
- ESANN 2017 - Fisher memory of linear Wigner echo state networks [Details]
- ESANN 2018 - Machine learning and data analysis in astroinformatics [Details]
- ESANN 2018 - Randomized Recurrent Neural Networks [Details]
- ESANN 2019 - Feature relevance bounds for ordinal regression [Details]
- ESANN 2002 - Free-swinging and locked joint fault detection and isolation in cooperative manipulators [Details]
- ESANN 1993 - Physiological modelling of cochlear nucleus responses-perception of complex sounds [Details]
- ESANN 1998 - Neural networks for financial forecast [Details]
- ESANN 1998 - Output jitter diverges to infinity, converges to zero or remains constant [Details]
- ESANN 2018 - Order Crossover for the Inventory Routing Problem [Details]
- ESANN 2005 - Relevance determination in reinforcement learning [Details]
- ESANN 2001 - Relevance determination in Learning Vector Quantization [Details]
- ESANN 2001 - SOM competition for complex image scene with variant object positions [Details]
- ESANN 2013 - Dimension reduction for individual ica to decompose FMRI during real-world experiences: principal component analysis vs. canonical correlation analysis [Details]
- ESANN 2020 - Handling missing data in recurrent neural networks for air quality forecasting [Details]
- ESANN 2024 - Deep Temporal Consensus Clustering for Patient Stratification in Amyotrophic Lateral Sclerosis [Details]
- ESANN 2009 - A semi-supervised approach to question classification [Details]
- ESANN 1999 - Marble slabs quality classification system using texture recognition and neural networks methodology [Details]
- ESANN 2014 - An Optimized Learning Algorithm Based on Linear Filters Suitable for Hardware implemented Self-Organizing Maps [Details]
- ESANN 2002 - Separation of a mixture of signals using linear filtering and second order statistics [Details]
- ESANN 2017 - Anomaly detection and characterization in smart card logs using NMF and Tweets [Details]
- ESANN 1993 - Trajectory learning using hierarchy of oscillatory modules [Details]
- ESANN 2015 - Gaussian process modelling of multiple short time series [Details]
- ESANN 2010 - Modeling contextualized textual knowledge as a Long-Term Working Memory [Details]
- ESANN 2003 - Anticipated synchronization in neuron models [Details]
- ESANN 1997 - From retinal circuits to motion processing: a neuromorphic approach to velocity estimation [Details]