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
Song Li
  • ESANN 2014 - Electric load forecasting using wavelet transform and extreme learning machine [Details]
Yuhua Li
  • ESANN 2014 - A new biologically plausible supervised learning method for spiking neurons [Details]
Shanglin Li
  • ESANN 2024 - Geometric Deep Learning to Enhance Imbalanced Domain Adaptation in EEG [Details]
Weizhi Li
  • ESANN 2017 - Learning convolutional neural network to maximize Pos@Top performance measure [Details]
Xue Li
  • ESANN 2025 - Continual Contrastive Learning on Tabular Data with Out of Distribution [Details]
Yichun Li
  • ESANN 2023 - Action-Based ADHD Diagnosis in Video [Details]
B. Li
  • ESANN 1995 - Spatial summation in simple cells: computational and experimental results [Details]
Xinjin Li
  • ESANN 2026 - Task-Specific Efficiency Analysis: When Small Language Models Outperform Large Language Models [Details]
Dingge Liang
  • ESANN 2022 - Deep latent position model for node clustering in graphs [Details]
Nanying Liang
  • ESANN 2009 - Decoding finger flexion using amplitude modulation from band-specific ECoG [Details]
Dingge Liang
  • No papers found
Yingyu Liang
  • ESANN 2016 - Learning in indefinite proximity spaces - recent trends [Details]
S.-C. Liao
  • ESANN 2000 - Fuzzy entropy-constrained competitive learning algorithm [Details]
G. Libert
  • ESANN 1993 - An efficient learning model for the neural integrator of the oculomotor system [Details]
  • ESANN 1995 - Active noise control with dynamic recurrent neural networks [Details]
  • ESANN 1995 - Identification of the human arm kinetics using dynamic recurrent neural networks [Details]
  • ESANN 1996 - Adaptative time constants improve the dynamic features of recurrent neural networks [Details]
  • ESANN 1996 - Negative initial weights improve learning in recurrent neural networks [Details]
  • ESANN 1997 - Evidence of efficiency of recurrent neural networks with ARMA-like units [Details]
Pieter Libin
  • ESANN 2019 - Deep hybrid approach for 3D plane segmentation [Details]
Pieter Libin
  • ESANN 2026 - Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance [Details]
Jiao Licheng
  • ESANN 2005 - A ridgelet kernel regression model using genetic algorithm [Details]
  • ESANN 2005 - Radar target recognition using SVMs with a wrapper feature selection driven by immune clonal algorithm [Details]
Robert Lieck
  • ESANN 2015 - Discovering temporally extended features for reinforcement learning in domains with delayed causalities [Details]
Yannic Lieder
  • ESANN 2021 - Constraint optimization for Echo State Networks applied to satellite image forecasting [Details]
S. Liehr
  • ESANN 1999 - Hidden Markov gating for prediction of change points in switching dynamical systems [Details]
Wei Shiung Liew
  • ESANN 2020 - Self-Organizing Kernel-based Convolutional Echo State Network for Human Actions Recognition [Details]
Elia Liitiäinen
  • ESANN 2006 - EM-algorithm for training of state-space models with application to time series prediction [Details]
  • ESANN 2007 - Nearest Neighbor Distributions and Noise Variance Estimation [Details]
  • ESANN 2008 - Using the Delta Test for Variable Selection [Details]
Jefrey Lijffijt
  • ESANN 2016 - Informative data projections: a framework and two examples [Details]
Konstantin K. Likharev
  • ESANN 2004 - Architectures for Nanoelectronic Neural Networks: New Results [Details]
Mariana Lilley
  • ESANN 2023 - On Instance Weighted Clustering Ensembles [Details]
D. Lim
  • ESANN 1998 - On the robust design of uncoupled CNNs [Details]
Sungwoo Lim
  • ESANN 2006 - Freeform surface induction from projected planar curves via neural networks [Details]
Ye-Sheen Lim
  • ESANN 2018 - Reinforcement Learning for High-Frequency Market Making [Details]
João J. G. Lima
  • ESANN 2024 - Leveraging Physics-Informed Neural Networks as Solar Wind Forecasting Models [Details]
Priscila Lima
  • No papers found