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
Barry O'Sullivan
- ESANN 2024 - SAT Instances Generation Using Graph Variational Autoencoders [Details]
- ESANN 2014 - Speedy greedy feature selection: Better redshift estimation via massive parallelism [Details]
- ESANN 2000 - Distributed clustering and local regression for knowledge discovery in multiple spatial databases [Details]
- ESANN 2009 - Studies on reservoir initialization and dynamics shaping in echo state networks [Details]
- ESANN 2005 - Support vector algorithms as regularization networks [Details]
- ESANN 2010 - Learning how to grasp objects [Details]
- ESANN 2015 - Bernoulli bandits: an empirical comparison [Details]
- ESANN 2000 - A new information criterion for the selection of subspace models [Details]
- ESANN 1997 - Exact asymptotic estimates of the storage capacities of the committee machines with overlapping and non-overlapping receptive fields [Details]
- ESANN 2000 - Toward encryption with neural network analogy [Details]
- ESANN 2013 - Ensembles of genetically trained artificial neural networks for survival analysis [Details]
- ESANN 2019 - Variational auto-encoders with Student’s t-prior [Details]
- ESANN 2020 - Cross-Encoded Meta Embedding towards Transfer Learning [Details]
- ESANN 1995 - On the function of the retinal bipolar cell in early vision [Details]
- ESANN 2010 - Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs [Details]
- ESANN 2023 - Knowledge Distillation for Anomaly Detection [Details]
- ESANN 1998 - Grouping complex face parts by nonlinear oscillations [Details]
- ESANN 2016 - Maximum likelihood learning of RBMs with Gaussian visible units on the Stiefel manifold [Details]
- ESANN 2021 - A Baseline for Shapley Values in MLPs: from Missingness to Neutrality [Details]
- ESANN 2006 - Selection of more than one gene at a time for cancer prediction from gene expression data [Details]
- ESANN 2003 - Classification of handwritten digits using supervised locally linear embedding algorithm and support vector machine [Details]
- ESANN 2001 - A computational model of monkey grating cells for oriented repetitive alternating patterns [Details]
- ESANN 2001 - Graph extraction from color images [Details]
- ESANN 2025 - Inferring Underwater Topography with Finite Volume Neural Networks [Details]
- ESANN 2001 - A novel chaotic neural network architecture [Details]
- ESANN 2002 - Learning in a chaotic neural network [Details]
- ESANN 2006 - Nonlinear dynamics in neural computation [Details]
- ESANN 2017 - Criticality in Biocomputation [Details]
- ESANN 2010 - Kernel generative topographic mapping [Details]
- ESANN 2010 - Segmentation of EMG time series using a variational Bayesian approach for the robust estimation of cortical silent periods [Details]
- ESANN 2010 - Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis [Details]
- ESANN 2011 - A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences [Details]
- ESANN 2021 - The partial response SVM [Details]
- ESANN 2018 - A variable projection method for block term decomposition of higher-order tensors [Details]
- ESANN 2016 - Semi-Supervised Classification of Social Textual Data Using WiSARD [Details]
- ESANN 2017 - Scholar Performance Prediction using Boosted Regression Trees Techniques [Details]
- ESANN 2017 - A decision support system based on cellular automata to help the control of late blight in tomato cultures [Details]
- ESANN 2017 - ELM vs. WiSARD: a performance comparison [Details]
- ESANN 2019 - Prediction of palm oil production with an enhanced n-Tuple Regression Network [Details]
- ESANN 2020 - Interpretation of Model Agnostic Classifiers via Local Mental Images [Details]