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Marek Śmieja
- ESANN 2020 - Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models [Details]
- ESANN 2020 - A preconditioned accelerated stochastic gradient descent algorithm [Details]
- ESANN 2013 - Mixed order associative networks for function approximation, optimisation and sampling [Details]
- ESANN 2001 - An alternative approach for the evaluation of the neocognitron [Details]
- ESANN 1993 - The filtered associative network [Details]
- ESANN 2002 - Stochastic resonance and finite resolution in a leaky integrate-and-fire neuron [Details]
- ESANN 2012 - Matrix relevance LVQ in steroid metabolomics based classification of adrenal tumors [Details]
- ESANN 2002 - Why will rat's go where rats will not? [Details]
- ESANN 2005 - Joint Regularization [Details]
- ESANN 2005 - Kernel methods and the exponential family [Details]
- ESANN 2020 - An agile machine learning project in pharma - developing a Mask R-CNN-based web application for bacterial colony counting [Details]
- ESANN 2020 - Deep Learning to Detect Bacterial Colonies for the Production of Vaccines [Details]
- ESANN 2020 - Machine learning in the biopharma industry [Details]
- ESANN 2019 - Machine learning in research and development of new vaccines products: opportunities and challenges [Details]
- ESANN 2018 - Structuring and Solving Multi-Criteria Decision Making Problems using Artificial Neural Networks: a smartphone recommendation case [Details]
- ESANN 2025 - Topology-Aware Activation Functions in Neural Networks [Details]
- ESANN 2014 - The one-sided mean kernel: a positive definite kernel for time series [Details]
- ESANN 2009 - Multiclass brain computer interface based on visual attention [Details]
- ESANN 2016 - Stacked denoising autoencoders for the automatic recognition of microglial cells’ state [Details]
- ESANN 1999 - A topological transformation for hidden recursive modelsarchitecture networks [Details]
- ESANN 2005 - Experimental validation of a synapse model by adding synaptic conductances to excitable endocrine cells in culture [Details]
- ESANN 2017 - Spikes as regularizers [Details]
- ESANN 2005 - A probabilistic framework for mismatch and profile string kernels [Details]
- ESANN 2009 - A neural model for binocular vergence control without explicit calculation of disparity [Details]
- ESANN 2010 - Neural models for the analysis of kidney disease patients [Details]
- ESANN 2000 - Parametric approach to blind deconvolution of nonlinear channels [Details]
- ESANN 2017 - Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification [Details]
- ESANN 2024 - EEG Source Imaging Enhances Motor Imagery Classification [Details]
- ESANN 1997 - Bayesian online learning in the perceptron [Details]
- ESANN 2007 - Spiral Recurrent Neural Network for Online Learning [Details]
- ESANN 2008 - Conditional prediction of time series using spiral recurrent neural network [Details]
- ESANN 1995 - Minimum entropy queries for linear students learning nonlinear rules [Details]
- ESANN 2003 - Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river [Details]
- ESANN 2000 - On the use of the wavelet decomposition for time series prediction [Details]
- ESANN 2009 - Sparse differential connectivity graph of scalp EEG for epileptic patients [Details]