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
Barbara Hammer
  • ESANN 2020 - Efficient computation of counterfactual explanations of LVQ models [Details]
  • ESANN 2020 - Locally Adaptive Nearest Neighbors [Details]
  • ESANN 2020 - Sparse Metric Learning in Prototype-based Classification [Details]
  • ESANN 2021 - Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting [Details]
  • ESANN 2021 - Federated Learning Vector Quantization [Details]
  • ESANN 2021 - Machine Learning for Measuring and Analyzing Online Social Communications [Details]
  • ESANN 2022 - Federated learning vector quantization for dealing with drift between nodes [Details]
  • ESANN 2022 - From hyperspectral to multispectral sensing – from simulation to reality: A comprehensive approach for calibration model transfer [Details]
  • ESANN 2022 - Improving Zorro Explanations for Sparse Observations with Dense Proxy Data [Details]
  • ESANN 2022 - Model Agnostic Local Explanations of Reject [Details]
  • ESANN 2022 - Neural Architecture Search for Sentence Classification with BERT [Details]
  • ESANN 2023 - On Feature Removal for Explainability in Dynamic Environments [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]
  • ESANN 2024 - Machine learning in distributed, federated and non-stationary environments - recent trends [Details]
  • ESANN 2024 - Noise Robust One-Class Intrusion Detection on Dynamic Graphs [Details]
  • ESANN 2024 - Self-Supervised Learning from Incrementally Drifting Data Streams [Details]
  • ESANN 2024 - Similarity-Based Zero-Shot Domain Adaptation for Wearables [Details]
  • ESANN 2024 - Trust in Artificial Intelligence: Beyond Interpretability [Details]
  • ESANN 2024 - Visualizing and Improving 3D Mesh Segmentation with DeepView [Details]
  • ESANN 2025 - Compression-based $k$NN for Class Incremental Continual Learning [Details]
  • ESANN 2025 - Conceptualizing Concept Drift [Details]
  • ESANN 2025 - Don't drift away: Advances and Applications of Streaming and Continual Learning [Details]
  • ESANN 2025 - Evaluating Concept Discovery Methods for Sensitive Attributes in Language Models [Details]
  • ESANN 2025 - Explaining Outliers using Isolation Forest and Shapley Interactions [Details]
  • ESANN 2025 - JEPA for RL: Investigating Joint-Embedding Predictive Architectures for Reinforcement Learning [Details]
  • ESANN 2025 - Solving Turbulent Rayleigh-Bénard Convection using Fourier Neural Operators [Details]
Barbara Hammer
  • ESANN 2004 - Neural methods for non-standard data [Details]
Barbara Hammer
  • ESANN 2021 - Concept Drift Segmentation via Kolmogorov-Trees [Details]
  • ESANN 2021 - Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data [Details]
  • ESANN 2022 - Contrasting Explanation of Concept Drift [Details]
  • ESANN 2023 - Feature Selection for Concept Drift Detection [Details]
  • ESANN 2024 - On the Fine Structure of Drifting Features [Details]
  • ESANN 2025 - Adversarial Attacks for Drift Detection [Details]
B. Hammer
  • ESANN 1998 - Training a sigmoidal network is difficult [Details]
  • ESANN 1999 - Approximation capabilities of folding networks [Details]
  • ESANN 2000 - Limitations of hybrid systems [Details]
  • ESANN 2001 - Input pruning for neural gas architectures [Details]
  • ESANN 2001 - Relevance determination in Learning Vector Quantization [Details]
  • ESANN 2002 - A general framework for unsupervised processing of structured data [Details]
  • ESANN 2002 - Batch-RLVQ [Details]
  • ESANN 2002 - Perspectives on learning with recurrent neural networks [Details]
  • ESANN 2003 - Improving iterative repair strategies for scheduling with the SVM [Details]
  • ESANN 2003 - Mathematical Aspects of Neural Networks [Details]
  • ESANN 2003 - Monitoring technical systems with prototype based clustering [Details]
  • ESANN 2003 - Unsupervised Recursive Sequence Processing [Details]
Christian Hammerschmidt
  • ESANN 2019 - time series modelling of market price in real-time bidding [Details]
Zahra HAMOU MAMAR
  • ESANN 2006 - Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system [Details]
Y. Han
  • ESANN 2002 - Forecasting using twinned principal curves [Details]
Long Han
  • ESANN 2006 - Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms [Details]
Azzag Hanane
  • ESANN 2012 - Automatic Group-Outlier Detection [Details]
  • ESANN 2019 - Deep Embedded SOM: joint representation learning and self-organization [Details]
Uwe Handmann
  • ESANN 2004 - Evolutionary Optimization of Neural Networks for Face Detection [Details]
  • ESANN 2015 - A simple technique for improving multi-class classification with neural networks [Details]
Uwe Handmann
  • No papers found
Uwe Handmann
  • ESANN 2022 - Battery detection of XRay images using transfer learning [Details]
  • ESANN 2023 - Don’t waste SAM [Details]
Jan Hanninen
  • ESANN 2016 - Comparison of Four- and Six-Layered Configurations for Deep Network Pretraining [Details]
Alexander Hans
  • ESANN 2008 - Safe exploration for reinforcement learning [Details]
  • ESANN 2010 - The Markov Decision Process Extraction Network [Details]
  • ESANN 2011 - Ensemble Usage for More Reliable Policy Identification in Reinforcement Learning [Details]
  • ESANN 2012 - Recurrent Neural State Estimation in Domains with Long-Term Dependencies [Details]
Michael Hanselmann
  • ESANN 2015 - Fast greedy insertion and deletion in sparse Gaussian process regression [Details]
Hans-Oliver Hansen
  • ESANN 2025 - Deciphering Barlow Twins: Reduncy Reduction is Insufficient and Normalization is Key [Details]
Lars Kai Hansen
  • No papers found
Richard Hanten
  • ESANN 2015 - Robust Visual Terrain Classification with Recurrent Neural Networks [Details]
Jin Hao
  • ESANN 2005 - Mutual information and gamma test for input selection [Details]
  • ESANN 2006 - Determination of the Mahalanobis matrix using nonparametric noise estimations [Details]
Mouloud Haouas
  • No papers found
Arsalan Haqqani
  • No papers found
David R. Hardoon
  • ESANN 2007 - A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning [Details]
Blake Hargis
  • ESANN 2010 - An augmented efficient backpropagation training strategy for deep autoassociative neural networks [Details]
Philip Harris
  • ESANN 2023 - Knowledge Distillation for Anomaly Detection [Details]
R. Harrison
  • ESANN 1999 - A kernel based adaline [Details]
  • ESANN 1999 - An efficient formulation of sparsity controlled support vector regression [Details]
Rachel Harrison
  • ESANN 2025 - Evolutionary Fault Localization Based on the Diversity of Suspiciousness Values [Details]
Rachel Harrison
  • ESANN 2018 - Evolutionary Composition of Customized Fault Localization Heuristics [Details]
Andreas Hartel
  • ESANN 2012 - Towards biologically realistic multi-compartment neuron model emulation in analog VLSI [Details]
Alexander Hartl
  • ESANN 2020 - SDOstream: Low-Density Models for Streaming Outlier Detection [Details]
Pitoyo Hartono
  • No papers found