Electronic proceedings author index

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
Xiang Jiang
  • ESANN 2017 - Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification [Details]
L. Jianyu
  • ESANN 2003 - Approximation of Function by Adaptively Growing Radial Basis Function Neural Networks [Details]
Licheng Jiao
  • ESANN 2005 - new evidences for sparse coding strategy employed in visual neurons: from the image processing and nonlinear approximation viewpoint [Details]
Pedro Jiménez García-Ligero
  • ESANN 2026 - Improving the Linearized Laplace Approximation via Quadratic Approximations [Details]
Yaochu Jin
  • ESANN 2005 - Efficient evolutionary optimization using individual-based evolution control and neural networks: A comparative study [Details]
Aashi Jindal
  • ESANN 2021 - Enhash: A Fast Streaming Algorithm For Concept Drift Detection [Details]
Wang Jing-Yan
  • ESANN 2017 - Learning convolutional neural network to maximize Pos@Top performance measure [Details]
Doreen Jirak
  • ESANN 2020 - New Results on Sparse Autoencoders for Posture Classification and Segmentation [Details]
Doreen Jirak
  • ESANN 2015 - Dynamic gesture recognition using Echo State Networks [Details]
Marcel Jirina
  • ESANN 2004 - Dimensionality reduction and classification using the distribution mapping exponent [Details]
Marcel Jiřina
  • ESANN 2020 - Unsupervised Latent Space Translation Network [Details]
Amal Jlassi
  • ESANN 2026 - XAI-Enabled Custom CNN for Cross-Modal Generalization in Breast Cancer Detection [Details]
Cezary Jochymski
  • ESANN 2009 - Application of SVM for cell recognition in BCC skin pathology [Details]
S. Joeken
  • ESANN 1995 - Predicting spike train responses of neuron models [Details]
Fabian Jogl
  • ESANN 2026 - GNNs Don't Need Backprop [Details]
Suykens Johan
  • ESANN 2014 - Agglomerative hierarchical kernel spectral clustering for large scale networks [Details]
  • ESANN 2014 - Optimal Data Projection for Kernel Spectral Clustering [Details]
  • ESANN 2014 - Reweighted l1 Dual Averaging Approach for Sparse Stochastic Learning [Details]
Anne Johannet
  • No papers found
Christopher Johansson
  • ESANN 2005 - Attractor neural networks with patchy connectivity [Details]
Lee John
  • ESANN 2020 - Deep Learning to Detect Bacterial Colonies for the Production of Vaccines [Details]
  • ESANN 2020 - Perplexity-free Parametric t-SNE [Details]
  • ESANN 2021 - Estimating uncertainty in radiation oncology dose prediction with dropout and bootstrap in U-Net models [Details]
  • ESANN 2021 - Impact of data subsamplings in Fast Multi-Scale Neighbor Embedding. [Details]
  • ESANN 2021 - Stochastic quartet approach for fast multidimensional scaling [Details]
  • ESANN 2022 - Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine [Details]
  • ESANN 2023 - Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration [Details]
  • ESANN 2023 - On the number of latent representations in deep neural networks for tabular data [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 2024 - Estimated neighbour sets and smoothed sampled global interactions are sufficient for a fast approximate tSNE. [Details]
  • ESANN 2024 - Forget early exaggeration in t-SNE: early hierarchization preserves global structure [Details]
  • ESANN 2024 - SDE U-Net: Disentangling Aleatoric and Epistemic Uncertainties in Medical Image Segmentation [Details]
  • ESANN 2025 - Can MDS rival with t-SNE by using the symmetric Kullback-Leibler divergence\\ across neighborhoods as a pseudo-distance? [Details]
  • ESANN 2026 - Fairness in machine learning: A Compact Survey [Details]
  • ESANN 2026 - Fast denoising of low-count Monte Carlo proton therapy dose distributions with ResUNet [Details]
  • ESANN 2026 - Interpretable Parametric Neighbour Embedding [Details]
  • ESANN 2026 - Multi-Scale Stochastic Neighbor Embedding with Twice Adaptive Bandwidths [Details]
  • ESANN 2026 - Towards meaningful evaluation of uncertainty-aware segmentation workflows for medical applications [Details]
LIZY JOHN
  • No papers found
LIZY JOHN
  • ESANN 2022 - A WiSARD-based conditional branch predictor [Details]
  • ESANN 2022 - Distributive Thermometer: A New Unary Encoding for Weightless Neural Networks [Details]
  • ESANN 2022 - Pruning Weightless Neural Networks [Details]
Garett Johnson
  • ESANN 2018 - interpretation of convolutional neural networks for speech regression from electrocorticography [Details]
Arnaud Joly
  • ESANN 2012 - L1-based compression of random forest models [Details]
P. D. Jones
  • ESANN 2003 - Statistical downscaling with artificial neural networks [Details]
Simon Jones
  • ESANN 2005 - predicting bed demand in a hospital using neural networks and ARIMA models: a hybrid approach [Details]
K. Jong
  • ESANN 2003 - Finding clusters using support vector classifiers [Details]
Marcel F. Jonkman
  • ESANN 2009 - Adaptive Metrics for Content Based Image Retrieval in Dermatology [Details]
Franz Joos
  • ESANN 2009 - The Use of ANN for Turbo Engine Applications [Details]
  • ESANN 2010 - Approximation of chemical reaction rates in turbulent combustion simulation [Details]
M. Joost
  • ESANN 1993 - Comparison of optimized backpropagation algorithms [Details]
Alexander I. Jordan
  • ESANN 2024 - Automatic Miscalibration Diagnosis: Interpreting Probability Integral Transform (PIT) Histograms [Details]