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Stefan Rotter
- ESANN 2011 - Increased robustness and intermittent dynamics in structured Reservoir Networks with feedback [Details]
- ESANN 1998 - Neural networks for financial forecast [Details]
- ESANN 2019 - Blind-spot network for image anomaly detection: A new approach to diabetic retinopathy screening [Details]
- ESANN 2004 - Reducing connectivity by using cortical modular bands [Details]
- ESANN 2023 - Comparative study of the synfire chain and ring attractor model for timing in the premotor nucleus in male Zebra Finches [Details]
- ESANN 2016 - How machine learning won the Higgs boson challenge [Details]
- ESANN 2018 - Systematics aware learning : a case study in high energy physics [Details]
- ESANN 2012 - The error-related potential and BCIs [Details]
- ESANN 2014 - Enhanced NMF initialization using a physical model for pollution source apportionment [Details]
- ESANN 2017 - Environmental signal processing: new trends and applications [Details]
- ESANN 2015 - Optimal transport for semi-supervised domain adaptation [Details]
- ESANN 2000 - Curve forecast with the SOM algorithm: using a tool to follow the time on a Kohonen map [Details]
- ESANN 2008 - A new method of DNA probes selection and its use with multi-objective neural network for predicting the outcome of breast cancer preoperative chemotherapy [Details]
- ESANN 1995 - Learning the appropriate representation paradigm by circular processing units [Details]
- ESANN 2011 - A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences [Details]
- ESANN 2001 - A structural genetic algorithm to optimize High Order Neural Network architecture [Details]
- ESANN 2004 - reduced dimensionality space for post placement quality inspection of components based on neural networks [Details]
- ESANN 2017 - Learning convolutional neural network to maximize Pos@Top performance measure [Details]
- ESANN 1997 - Nonlinearity and separation capability: further justification for the ICA algorithm with a learned mixture of parametric densities [Details]
- ESANN 2009 - Applying Mutual Information for Prototype or Instance Selection in Regression Problems [Details]
- ESANN 2002 - A reconfigurable SOM hardware accelerator [Details]
- ESANN 2006 - Robust Local Cluster Neural Networks [Details]
- ESANN 2007 - Controlling complexity of RBF networks by similarity [Details]
- ESANN 2012 - Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting [Details]
- ESANN 2012 - Parallel neural hardware: the time is right [Details]
- ESANN 2012 - gNBXe -- a Reconfigurable Neuroprocessor for Various Types of Self-Organizing Maps [Details]
- ESANN 1994 - A stop criterion for the Boltzmann machine learning algorithm [Details]
- ESANN 2019 - Pixel-wise Conditioning of Generative Adversarial Networks [Details]
- ESANN 1996 - An analysis of the metric structure of the weight space of feedforward networks and its application to time series modeling and prediction [Details]
- ESANN 2009 - SVM-based learning method for improving colour adjustment in automotive basecoat manufacturing [Details]
- ESANN 2011 - The role of Fisher information in primary data space for neighbourhood mapping [Details]
- ESANN 2012 - Constructing similarity networks using the Fisher information metric [Details]
- ESANN 2015 - Measuring scoring efficiency through goal expectancy estimation [Details]
- ESANN 2013 - A quotient basis kernel for the prediction of mortality in severe sepsis patients [Details]
- ESANN 2014 - Exploiting similarity in system identification tasks with recurrent neural networks [Details]
- ESANN 2018 - Sensitivity analysis for predictive uncertainty [Details]
- ESANN 2019 - interpretable dynamics models for data-efficient reinforcement learning [Details]
- ESANN 2021 - Behavior Constraining in Weight Space for Offline Reinforcement Learning [Details]
- ESANN 2021 - Differentially Private Time Series Generation [Details]
- ESANN 2023 - Automatic Trade-off Adaptation in Offline RL [Details]
- ESANN 2020 - Cost-free resolution enhancement in Convolutional Neural Networks for medical image segmentation [Details]
- ESANN 1999 - Regularization in oculomotor adaptation [Details]