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Mark Hereld
- ESANN 2009 - Oscillation in a network model of neocortex [Details]
- ESANN 2018 - interpretation of convolutional neural networks for speech regression from electrocorticography [Details]
- ESANN 2016 - Multispectral Pedestrian Detection using Deep Fusion Convolutional Neural Networks [Details]
- ESANN 2016 - Simultaneous estimation of rewards and dynamics from noisy expert demonstrations [Details]
- ESANN 2017 - Learning Semantic Prediction using Pretrained Deep Feedforward Networks [Details]
- ESANN 2018 - Hierarchical Recurrent Filtering for Fully Convolutional DenseNets [Details]
- ESANN 2021 - Semi-supervised learning with Bayesian Confidence Propagation Neural Network [Details]
- ESANN 2023 - Spiking neural networks with Hebbian plasticity for unsupervised representation learning [Details]
- ESANN 2012 - Integration of Structural Expert Knowledge about Classes for Classification Using the Fuzzy Supervised Neural Gas [Details]
- ESANN 2014 - Optimization of General Statistical Accuracy Measures for Classification Based on Learning Vector Quantization [Details]
- ESANN 2018 - Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach [Details]
- ESANN 2003 - Neural networks organizations to learn complex robotic functions [Details]
- ESANN 2021 - Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting [Details]
- ESANN 2024 - Noise Robust One-Class Intrusion Detection on Dynamic Graphs [Details]
- ESANN 2012 - learning task relatedness via dirichlet process priors for linear regression models [Details]
- ESANN 1998 - On the error function of interval arithmetic backpropagation [Details]
- ESANN 1998 - One or two hidden layers perceptrons [Details]
- ESANN 2012 - Similarity networks for heterogeneous data [Details]
- ESANN 2000 - Influence of weight-decay training in input selection methods [Details]
- ESANN 2001 - Coding the outputs of multilayer feedforward [Details]
- ESANN 2001 - Weight initialization methods for multilayer feedforward [Details]
- ESANN 2003 - A new rule extraction algorithm based on interval arithmetic [Details]
- ESANN 2003 - Ensemble Methods for Multilayer Feedforward [Details]
- ESANN 2012 - On the Independence of the Individual Predictions in Parallel Randomized Ensembles [Details]
- ESANN 2024 - Joint Entropy Search for Multi-objective Bayesian Optimization with Constraints and Multiple Fidelities [Details]
- ESANN 2018 - Sensitivity analysis for predictive uncertainty [Details]
- ESANN 2021 - Federated Learning approach for SpectralClustering [Details]
- ESANN 2023 - Evaluating Curriculum Learning Strategies for Pancreatic Cancer Prediction [Details]
- ESANN 2024 - AI-based algorithm for intrusion detection on a real dataset [Details]
- ESANN 2016 - Automatic detection of EEG arousals [Details]
- ESANN 2017 - Outlining a simple and robust method for the automatic detection of EEG arousals [Details]
- ESANN 2018 - Sleep staging with deep learning: a convolutional model [Details]
- ESANN 2004 - MultiGrid-Based Fuzzy Systems for Time Series: Forecasting: Overcoming the curse of dimensionality [Details]
- ESANN 2009 - Applying Mutual Information for Prototype or Instance Selection in Regression Problems [Details]
- No papers found
- ESANN 2004 - Visual person tracking with a Supervised Conditioning-SOM [Details]
- ESANN 2005 - The architecture of emergent self-organizing maps to reduce projection errors [Details]
- ESANN 2008 - Explaining Ant-Based Clustering on the basis of Self-Organizing Maps [Details]
- ESANN 1994 - Instabilities in self-organized feature maps with short neighbourhood range [Details]
- ESANN 1997 - Measuring topology preservation in maps of real-world data [Details]
- ESANN 1998 - Magnification control in neural maps [Details]
- ESANN 2001 - A two steps method: non linear regression and pruning neural network for analyzing multicomponent mixtures [Details]
- ESANN 2001 - Genetic algorithms with crossover based on confidence interval as an alternative to traditional nonlinear regression methods [Details]
- ESANN 2013 - Multi-scale Support Vector Machine Optimization by Kernel Target-Alignment [Details]
- ESANN 2013 - Synthetic over-sampling in the empirical feature space [Details]
- ESANN 2004 - Modelling of biologically plausible excitatory networks: emergence and modulation of neural synchrony [Details]
- ESANN 2005 - Spike-timing-dependent plasticity in 'small world' networks [Details]
- ESANN 2006 - Connection strategies in neocortical networks [Details]
- ESANN 2007 - Transition from initialization to working stage in biologically realistic networks [Details]
- ESANN 2008 - Simulation of a recurrent neurointerface with sparse electrical connections [Details]
- ESANN 2004 - Learning by geometrical shape changes of dendritic spines [Details]
- ESANN 2004 - Novel approximations for inference and learning in nonlinear dynamical systems [Details]
- ESANN 2009 - Exploring the impact of alternative feature representations on BCI classification [Details]
- ESANN 2009 - Multi-task Preference learning with Gaussian Processes [Details]
- ESANN 2011 - A structure independent algorithm for causal discovery [Details]
- ESANN 2011 - Learning of causal relations [Details]
- ESANN 1994 - Stochastics of on-line back-propagation [Details]
- ESANN 1999 - Model clustering by deterministic annealing [Details]
- ESANN 2000 - An optimization neural network model with time-dependent and lossy dynamics [Details]
- ESANN 2024 - Predicting the Closing Cross Auction Results at the NASDAQ Stock Exchange [Details]
- ESANN 2019 - Reactive Soft Prototype Computing for frequent reoccurring Concept Drift [Details]