A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z
A. Thiel
- ESANN 2001 - Extracting motion information using a biologically realistic model retina [Details]
- ESANN 2021 - Distribution Preserving Multiple Hypotheses Prediction for Uncertainty Modeling [Details]
- ESANN 1993 - Self-organization of a Kohonen network with quantized weights and a arbitrary one-dimensional stimuli distribution [Details]
- ESANN 2004 - Visualization and classification with categorical topological map [Details]
- ESANN 2005 - Mixed Topological Map [Details]
- ESANN 1997 - Probabilistic self organized map - application to classification [Details]
- ESANN 2000 - Topological map for binary data [Details]
- ESANN 1993 - Optimal decision surfaces in LVQ1 classiffication of patterns [Details]
- ESANN 1995 - Suboptimal Bayesian classification by vector quantization with small clusters [Details]
- ESANN 1998 - A multistage on-line learning rule for multilayer neural network [Details]
- ESANN 2014 - Evidence build-up facilitates on-line adaptivity in dynamic environments: example of the BCI P300-speller [Details]
- ESANN 1994 - Stability and bifurcation in an autoassociative memory model [Details]
- ESANN 2007 - Transition from initialization to working stage in biologically realistic networks [Details]
- ESANN 2023 - Exploring Strategies for Modeling Sign Language Phonology [Details]
- ESANN 2019 - Using Deep Learning and Evolutionary Algorithms for Time Series Forecasting [Details]
- ESANN 2012 - Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm [Details]
- ESANN 2014 - Implicitly and explicitly constrained optimization problems for training of recurrent neural networks [Details]
- ESANN 1997 - How can the visual system process a natural scene in under 150ms? On the role of asynchronous spike propagation [Details]
- ESANN 2019 - Knowledge Discovery in Quarterly Financial Data of Stocks Based on the Prime Standard using a Hybrid of a Swarm with SOM [Details]
- ESANN 2011 - A Multi-kernel Framework for Inductive Semi-supervised Learning [Details]
- ESANN 2014 - Using Shannon Entropy as EEG Signal Feature for Fast Person Identification [Details]
- ESANN 2002 - Yield curve forecasting by error correction neural networks and partial learning [Details]
- ESANN 2020 - Handling missing data in recurrent neural networks for air quality forecasting [Details]
- ESANN 2008 - Selection of important input variables for RBF network using partial derivatives [Details]
- ESANN 2003 - Road Singularities Detection and Classification [Details]
- ESANN 2020 - Weighted Emprirical Risk Minimization: Transfer Learning based on Importance Sampling [Details]
- 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]