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
Benjamin Paaßen
  • ESANN 2019 - Dynamic fairness - Breaking vicious cycles in automatic decision making [Details]
  • ESANN 2019 - Embeddings and Representation Learning for Structured Data [Details]
Benjamin Paassen
  • ESANN 2014 - Adaptive distance measures for sequential data [Details]
  • ESANN 2015 - Adaptive structure metrics for automated feedback provision in Java programming [Details]
  • ESANN 2016 - Gaussian process prediction for time series of structured data [Details]
  • ESANN 2017 - An EM transfer learning algorithm with applications in bionic hand prostheses [Details]
Benjamin Paassen
  • ESANN 2024 - Few-shot similarity learning for motion classification via electromyography [Details]
  • ESANN 2024 - Tumor Grading via Decorrelated Sparse Survival Regression [Details]
  • ESANN 2025 - Linear Domain Adaptation for Robustness to Electrode Shifts [Details]
Benjamin Paassen
  • ESANN 2020 - Reservoir memory machines [Details]
Benjamin Paassen
  • ESANN 2021 - Deep learning for graphs [Details]
Marco Aurélio Pacheco
  • ESANN 2004 - Data Mining Techniques on the Evaluation of Wireless Churn [Details]
Mithila Packiyanathan
  • ESANN 2024 - Exploring High- and Low-Density Electroencephalography for a Dream Decoding Brain-Computer Interface [Details]
  • ESANN 2024 - Unveiling Dreams: Moving Towards Automatic Dream Decoding via PSD-Based EEG Analysis and Machine Learning [Details]
G. Pagès
  • ESANN 1993 - Voronoï tesselation, space quantization algorithms and numerical integration [Details]
  • ESANN 1994 - A non linear Kohonen algorithm [Details]
  • ESANN 1994 - Two or three things that we know about the Kohonen algorithm [Details]
  • ESANN 1995 - About the Kohonen algorithm: strong or weak self-organization? [Details]
  • ESANN 1995 - Functional approximation by perceptrons: a new approach [Details]
  • ESANN 1996 - On the critical points of the 1-dimensional competitive learning vector quantization algorithm [Details]
  • ESANN 1996 - Quantization vs Organization in the Kohonen S.O.M. [Details]
  • ESANN 1997 - Almost sure convergence of the one-dimensional Kohonen algorithm [Details]
M. Paindavoine
  • ESANN 1998 - Face recognition: pre-processing techniques for linear autoassociators [Details]
Joao Paixao
  • ESANN 2018 - Vector Field Based Neural Networks [Details]
Joni Pajarinen
  • No papers found
Joni Pajarinen
  • ESANN 2022 - Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning [Details]
P. Pajunen
  • ESANN 1997 - A competitive learning algorithm for separating binary sources [Details]
Arpan Pal
  • ESANN 2019 - Fusing Features based on Signal Properties and TimeNet for Time Series Classification [Details]
Arpan Pal
  • No papers found
Amit Kumar Pal
  • ESANN 2025 - Early Prediction of Dynamic Sparsity in Large Language Models [Details]
Arpan Pal
  • ESANN 2022 - Appearance-Context aware Axial Attention for Fashion Landmark Detection [Details]
P.M. Palagi
  • ESANN 1996 - Interpreting data through neural and statistical tools [Details]
Lorenzo Paletto
  • ESANN 2023 - Hierarchical priors for Hyperspherical Prototypical Networks [Details]
Pantita Palittapongarnpim
  • ESANN 2016 - Controlling adaptive quantum-phase estimation with scalable reinforcement learning [Details]
Shubham Paliwal
  • ESANN 2021 - TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words [Details]
M. Pallavicini
  • ESANN 1999 - Support vector machines vs multi-layer perceptrons in particle identification [Details]
Günther Palm
  • ESANN 2008 - Detecting zebra crossings utilizing AdaBoost [Details]
  • ESANN 2008 - Multi-View Forests of Tree-Structured Radial Basis Function Networks Based on Dempster-Shafer Evidence Theory [Details]
  • ESANN 2008 - Word recognition and incremental learning based on neural associative memories and hidden Markov models [Details]
  • ESANN 2015 - SMO Lattices for the Parallel Training of Support Vector Machines [Details]
Giulia Palma
  • ESANN 2025 - Introducing Intrinsic Motivation in Elastic Decision Transformers [Details]
Sam Palmer
  • ESANN 2017 - Pseudo-analytical solutions for stochastic options pricing using Monte Carlo simulation and Breeding PSO-trained neural networks [Details]
F. Palmieri
  • ESANN 1999 - Generalized support vector machines [Details]
  • ESANN 1999 - Independent component analysis for mixture densities [Details]
Esteban Palomo
  • ESANN 2010 - An ART-type network approach for video object detection [Details]
  • ESANN 2010 - Web Document Clustering based on a Hierarchical Self-Organizing Model [Details]
Jiajun Pan
  • ESANN 2019 - Metric learning with relational data [Details]
  • ESANN 2019 - Metric learning with submodular functions [Details]
Christos Panayiotou
  • ESANN 2024 - Self-Supervised Learning from Incrementally Drifting Data Streams [Details]
Patrick Panciatici
  • ESANN 2018 - Fast Power system security analysis with Guided Dropout [Details]
  • ESANN 2019 - LEAP nets for power grid perturbations [Details]