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
Mohamed Jabri
  • ESANN 2024 - Invariant Representation Learning for Generalizable Imitation [Details]
L. Jack
  • ESANN 1999 - Feature selection for ANNs using genetic algorithms in condition monitoring [Details]
Julien Jacques
  • ESANN 2012 - Curves clustering with approximation of the density of functional random variables [Details]
Laurent Jacques
  • ESANN 2020 - Compressive Learning of Generative Networks [Details]
  • ESANN 2022 - ROP inception: signal estimation with quadratic random sketching [Details]
Laurent Jacques
  • ESANN 2017 - Piecewise-Bézier C1 smoothing on manifolds with application to wind field estimation [Details]
Philippe Jacquet
  • ESANN 2020 - On Feature Selection Using Anisotropic General Regression Neural Network [Details]
Herbert Jaeger
  • ESANN 2012 - Theory of Input Driven Dynamical Systems [Details]
Grégoire JAFFRE
  • ESANN 2023 - TabSRA: An Attention based Self-Explainable Model for Tabular Learning [Details]
Andeas Jahn
  • ESANN 2011 - Fast Data Mining with Sparse Chemical Graph Fingerprints by Estimating the Probability of Unique Patterns [Details]
B.J. Jain
  • ESANN 2001 - On the short-term-memory of WTA nets [Details]
  • ESANN 2003 - A Neural Graph Isomorphism Algorithm based on local Invariants [Details]
  • ESANN 2003 - An Associative Memory for the Automorphism Group of Structures [Details]
Abha Jain
  • ESANN 2004 - Forbidden Magnification? I. [Details]
Abha Jain
  • ESANN 2004 - Forbidden magnification? II. [Details]
Brijnesh J. Jain
  • ESANN 2004 - The maximum weighted clique problem and Hopfield networks [Details]
Brijnesh J. Jain
  • ESANN 2004 - SVM learning with the SH inner product [Details]
Brijnesh J. Jain
  • ESANN 2004 - Neural methods for non-standard data [Details]
Arushi Jain
  • ESANN 2021 - TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words [Details]
Hunor Jakab
  • ESANN 2012 - Manifold-based non-parametric learning of action-value functions [Details]
Jens Jäkel
  • ESANN 2023 - Robust and Cheap Safety Measure for Exoskeletal Learning Control with Estimated Uniform PAC (EUPAC) [Details]
Jonathan Jakob
  • ESANN 2019 - Feature relevance bounds for ordinal regression [Details]
Matthias Jakobs
  • ESANN 2024 - Federated Time Series Classification with ROCKET features [Details]
Brayan James
  • ESANN 2019 - Weightless neural systems for deforestation surveillance and image-based navigation of UAVs in the Amazon forest [Details]
Waqas Jamil
  • ESANN 2019 - Online Bayesian Shrinkage Regression [Details]
N. Jankowski
  • ESANN 2001 - Optimal transfer function neural networks [Details]
  • ESANN 2001 - Transfer functions: hidden possibilities for better neural networks [Details]
Peter Jansen
  • ESANN 2018 - Temporal transfer learning for drift adaptation [Details]
Walter Jansen
  • ESANN 2013 - Prior knowledge in an end-user trainable machine vision framework [Details]
Dominik Janzing
  • ESANN 2007 - Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions [Details]
  • ESANN 2007 - Exploring the causal order of binary variables via exponential hierarchies of Markov kernels [Details]
  • ESANN 2007 - Learning causality by identifying common effects with kernel-based dependence measures [Details]
M.A. Jaramillo-Moran
  • ESANN 1994 - A general model for higher order neurons [Details]
Ian Jarman
  • 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]
Ian H. Jarman
  • ESANN 2016 - Performance assessment of quantum clustering in non-spherical data distributions [Details]
Sarah Jarvis
  • ESANN 2011 - Increased robustness and intermittent dynamics in structured Reservoir Networks with feedback [Details]