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Irina Abnizova
- ESANN 2008 - Discrimination of regulatory DNA by SVM on the basis of over- and under-represented motifs [Details]
- ESANN 2022 - Battery detection of XRay images using transfer learning [Details]
- ESANN 2023 - Don’t waste SAM [Details]
- No papers found
- ESANN 2018 - Interpreting deep learning models for ordinal problems [Details]
- ESANN 2023 - Coordinate descent on the Stiefel manifold for deep neural network training [Details]
- ESANN 2022 - Gap filling in air temperature series by matrix completion methods [Details]
- ESANN 2023 - An Alternating Minimization Algorithm with Trajectory for Direct Exoplanet Detection [Details]
- ESANN 2025 - Exoplanet detection in angular and spectral differential imaging with an accelerated proximal gradient algorithm [Details]
- ESANN 2013 - A nuclear-norm based convex formulation for informed source separation [Details]
- ESANN 2013 - ONP-MF: An Orthogonal Nonnegative Matrix Factorization Algorithm with Application to Clustering [Details]
- ESANN 2009 - Gene expression data analysis using spatiotemporal blind source separation [Details]
- ESANN 2010 - Oriented Bounding Box Computation Using Particle Swarm Optimization [Details]
- ESANN 2012 - Range-based non-orthogonal ICA using cross-entropy method [Details]
- ESANN 2014 - Capturing confounding sources of variation in DNA methylation data by spatiotemporal independent component analysis [Details]
- ESANN 2015 - Rank-constrained optimization: a Riemannian manifold approach [Details]
- ESANN 2016 - Differentiable piecewise-Bézier interpolation on Riemannian manifolds [Details]
- ESANN 2016 - Extending a two-variable mean to a multi-variable mean [Details]
- ESANN 2016 - Spatiotemporal ICA improves the selection of differentially expressed genes [Details]
- ESANN 2017 - Learning sparse models of diffusive graph signals [Details]
- ESANN 2017 - Piecewise-Bézier C1 smoothing on manifolds with application to wind field estimation [Details]
- ESANN 2018 - A variable projection method for block term decomposition of higher-order tensors [Details]
- ESANN 2019 - Interpolation on the manifold of fixed-rank positive-semidefinite matrices for parametric model order reduction: preliminary results [Details]
- ESANN 2019 - Minimax center to extract a common subspace from multiple datasets [Details]
- ESANN 2019 - Preconditioned conjugate gradient algorithms for graph regularized matrix completion [Details]
- No papers found
- ESANN 1994 - A general model for higher order neurons [Details]
- ESANN 1999 - Modeling face recognition learning in early infant development [Details]
- ESANN 2003 - Neural Net with Two Hidden Layers for Non-Linear Blind Source Separation [Details]
- ESANN 2020 - Weighted Emprirical Risk Minimization: Transfer Learning based on Importance Sampling [Details]
- ESANN 2009 - Sparse differential connectivity graph of scalp EEG for epileptic patients [Details]
- ESANN 2017 - Impact of the initialisation of a blind unmixing method dealing with intra-class variability [Details]
- ESANN 2025 - Robust Evolutionary Multi-Objective Neural Architecture Search for Reinforcement Learning (EMNAS-RL) [Details]
- ESANN 2016 - Initializing nonnegative matrix factorization using the successive projection algorithm for multi-parametric medical image segmentation [Details]
- ESANN 2025 - Generative Kernel Spectral Clustering [Details]
- ESANN 2013 - Automatic Singular Spectrum Analysis for Time-Series Decomposition [Details]
- ESANN 2013 - Normalized cuts clustering with prior knowledge and a pre-clustering stage [Details]
- ESANN 2016 - Initializing nonnegative matrix factorization using the successive projection algorithm for multi-parametric medical image segmentation [Details]
- ESANN 2016 - Deep multi-task learning with evolving weights [Details]
- ESANN 2025 - 3-WL GNNs for Metric Learning on Graphs [Details]
- ESANN 2016 - How machine learning won the Higgs boson challenge [Details]
- ESANN 2023 - Sleep analysis in a CLIS patient using soft-clustering: a case study [Details]
- ESANN 1997 - Extraction of crisp logical rules using constrained backpropagation networks [Details]
- ESANN 2001 - Constructive density estimation network based on several different separable transfer functions [Details]
- ESANN 2004 - Non-Euclidean norms and data normalisation [Details]
- ESANN 2005 - TreeGNG - hierarchical topological clustering [Details]
- ESANN 2006 - Gaussian and exponential architectures in small-world associative memories [Details]
- ESANN 2006 - Topological Correlation [Details]
- ESANN 2006 - Using sampling methods to improve binding site predictions [Details]
- ESANN 2007 - Sparsely-connected associative memory models with displaced connectivity [Details]
- ESANN 2008 - Using graph-theoretic measures to predict the performance of associative memory models [Details]
- ESANN 2009 - Connection strategy and performance in sparsely connected 2D associative memory models with non-random images [Details]
- ESANN 2010 - The Application of Gaussian Processes in the Prediction of Percutaneous Absorption for Mammalian and Synthetic Membranes [Details]
- ESANN 2017 - Investigating optical transmission error correction using wavelet transforms [Details]
- ESANN 2023 - Probabilistic Adaptation for Meta-Learning [Details]
- ESANN 2015 - Improving the random forest algorithm by randomly varying the size of the bootstrap samples for low dimensional data sets [Details]
- ESANN 2015 - One-vs-all binarization technique in the context of random forest [Details]
- ESANN 2017 - Automatic crime report classi cation through a weightless neural network [Details]
- ESANN 2004 - Neural Hardware: beyond ones and zeros [Details]