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
U.-D. Braumann
  • ESANN 1995 - An episodic knowledge base for object understanding [Details]
Katharina Braun
  • ESANN 2004 - Learning by geometrical shape changes of dendritic spines [Details]
R. Brause
  • ESANN 2000 - A neuro-fuzzy approach as medical diagnostic interface [Details]
A. Bray
  • ESANN 2002 - Kernel Temporal Component Analysis (KTCA) [Details]
Massimo Brescia
  • ESANN 2018 - stellar formation rates in galaxies using machine learning models [Details]
Bastien Breteau
  • ESANN 2011 - Approaches for Automatic Speaker Recognition in a Binaural Humanoid Context [Details]
Maurício Breternitz
  • ESANN 2019 - Memory Efficient Weightless Neural Network using Bloom Filter [Details]
Mauricio Breternitz Jr.
  • No papers found
Mauricio Breternitz Jr.
  • 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]
  • ESANN 2023 - Efficient Knowledge Aggregation Methods for Weightless Neural Networks [Details]
S. Breutel
  • ESANN 2003 - Extracting Interface Assertions from Neural Networks in Polyhedral Format [Details]
B. Breznen
  • ESANN 1993 - Place-to-time code transformation during saccades [Details]
Hans Briegel
  • ESANN 2016 - Enhanced learning for agents in quantum-accessible environments [Details]
Rodrigo Brindeiro
  • ESANN 2012 - Recognition of HIV-1 subtypes and antiretroviral drug resistance using weightless neural networks [Details]
Johannes Brinkrolf
  • ESANN 2018 - Differential private relevance learning [Details]
Johannes Brinkrolf
  • ESANN 2020 - Sparse Metric Learning in Prototype-based Classification [Details]
  • ESANN 2021 - Federated Learning Vector Quantization [Details]
  • ESANN 2022 - Federated learning vector quantization for dealing with drift between nodes [Details]
  • ESANN 2023 - Robust Feature Selection and Robust Training to Cope with Hyperspectral Sensor Shifts [Details]
  • ESANN 2024 - Causes of Rejects in Prototype-based Classification Aleatoric vs. Epistemic Uncertainty [Details]
Xavier BRIOTTET
  • ESANN 2017 - Impact of the initialisation of a blind unmixing method dealing with intra-class variability [Details]
Walkir Brito
  • ESANN 2017 - Automatic crime report classi cation through a weightless neural network [Details]
Lucas Brito Silva
  • ESANN 2023 - Large-scale dataset and benchmarking for hand and face detection focused on sign language [Details]
Alceu de Souza Britto Jr.
  • No papers found
Alceu de Souza Britto Jr.
  • ESANN 2022 - A Machine Learning Approach for School Dropout Prediction in Brazil [Details]
Felicitas Brokmann
  • ESANN 2025 - Investigating the Impact of Imbalanced Medical Data on the Performance of Self-Supervised Learning Approaches [Details]
Stefano Bromuri
  • ESANN 2023 - Graph-based Categorical Embedding [Details]
  • ESANN 2023 - Language Modeling in Logistics: Customer Calling Prediction [Details]
Chris Bronk
  • ESANN 2021 - Machine Learning for Measuring and Analyzing Online Social Communications [Details]
Johanna Bronner
  • ESANN 2021 - Differentially Private Time Series Generation [Details]
Mats Brorsson
  • ESANN 2019 - time series modelling of market price in real-time bidding [Details]
Maximilian Broß
  • ESANN 2023 - Segmentation and Analysis of Lumbar Spine MRI Scans for Vertebral Body Measurements [Details]
R. K. Brouwer
  • ESANN 1999 - An integer recurrent artificial neural network for classifying feature vectors [Details]
  • ESANN 2001 - One-to-many mappings represented on feed-forward networks [Details]
R.K. Brouwer
  • ESANN 2002 - Storing many-to-many mappings on a feed-forward neural network using fuzzy sets [Details]
Marc Brown
  • ESANN 2010 - The Application of Gaussian Processes in the Prediction of Percutaneous Absorption for Mammalian and Synthetic Membranes [Details]
D. Brown
  • ESANN 1998 - Output jitter diverges to infinity, converges to zero or remains constant [Details]
  • ESANN 1998 - What is observable in a class of neurodynamics? [Details]