Neural networks for pattern recognition

Citation edge evidence

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• A Tutorial on Support Vector Machines for Pattern Recognition→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Gaussian Processes for Machine Learning→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Bidirectional recurrent neural networks→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• The Graph Neural Network Model→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Least Squares Support Vector Machine Classifiers→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Segmentation of brain MR images through a hidden Markov random field model and the expect…→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Pattern Recognition and Neural Networks→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Survey of Clustering Algorithms→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Framewise phoneme classification with bidirectional LSTM and other neural network archite…→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Connectionist temporal classification→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Support Vector Data Description→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• An introduction to kernel-based learning algorithms→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• A Survey of Outlier Detection Methodologies→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Artificial neural networks: fundamentals, computing, design, and application→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• On hyperparameter optimization of machine learning algorithms: Theory and practice→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Algorithms for Hyper-Parameter Optimization→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Methods for interpreting and understanding deep neural networks→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Dynamic bayesian networks: representation, inference and learning→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• A gentle tutorial of the em algorithm and its application to parameter estimation for Gau…→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Logistic regression and artificial neural network classification models: a methodology re…→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• KNN Model-Based Approach in Classification→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• LSTM neural networks for language modeling→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Mixtures of Probabilistic Principal Component Analyzers→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Variational Algorithms for Approximate Bayesian Inference→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• The k-means Algorithm: A Comprehensive Survey and Performance Evaluation→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Neural networks for classification: a survey→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Ensemble Machine Learning→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• On the mathematical foundations of learning→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• An analysis of particle swarm optimizers→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Explaining nonlinear classification decisions with deep Taylor decomposition→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• GTM: The Generative Topographic Mapping→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• A gentle tutorial of the em algorithm and its application to parameter estimation for Gau…→GTM: The Generative Topographic MappingLegacy edge — source detail unavailable
• A gentle tutorial of the em algorithm and its application to parameter estimation for Gau…→Pattern Recognition and Neural NetworksLegacy edge — source detail unavailable
• Gaussian Processes for Machine Learning→GTM: The Generative Topographic MappingLegacy edge — source detail unavailable
• Gaussian Processes for Machine Learning→Pattern Recognition and Neural NetworksLegacy edge — source detail unavailable
• Support Vector Data Description→Pattern Recognition and Neural NetworksLegacy edge — source detail unavailable
• Logistic regression and artificial neural network classification models: a methodology re…→Pattern Recognition and Neural NetworksLegacy edge — source detail unavailable
• Framewise phoneme classification with bidirectional LSTM and other neural network archite…→Bidirectional recurrent neural networksLegacy edge — source detail unavailable
• Algorithms for Hyper-Parameter Optimization→Gaussian Processes for Machine LearningLegacy edge — source detail unavailable
• GTM: The Generative Topographic Mapping→Mixtures of Probabilistic Principal Component AnalyzersLegacy edge — source detail unavailable
• An introduction to kernel-based learning algorithms→A Tutorial on Support Vector Machines for Pattern RecognitionLegacy edge — source detail unavailable
• Variational Algorithms for Approximate Bayesian Inference→Mixtures of Probabilistic Principal Component AnalyzersLegacy edge — source detail unavailable
• Connectionist temporal classification→Framewise phoneme classification with bidirectional LSTM and other neural network archite…Legacy edge — source detail unavailable
• Connectionist temporal classification→Bidirectional recurrent neural networksLegacy edge — source detail unavailable
• Mixtures of Probabilistic Principal Component Analyzers→GTM: The Generative Topographic MappingLegacy edge — source detail unavailable
• Survey of Clustering Algorithms→An introduction to kernel-based learning algorithmsLegacy edge — source detail unavailable
• Survey of Clustering Algorithms→A Tutorial on Support Vector Machines for Pattern RecognitionLegacy edge — source detail unavailable
• On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation→Pattern Recognition and Neural NetworksLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Pattern Recognition and Neural NetworksLegacy edge — source detail unavailable
• Explaining nonlinear classification decisions with deep Taylor decomposition→Gaussian Processes for Machine LearningLegacy edge — source detail unavailable
• Explaining nonlinear classification decisions with deep Taylor decomposition→An introduction to kernel-based learning algorithmsLegacy edge — source detail unavailable
• LSTM neural networks for language modeling→Framewise phoneme classification with bidirectional LSTM and other neural network archite…Legacy edge — source detail unavailable
• Ensemble Machine Learning→Pattern Recognition and Neural NetworksLegacy edge — source detail unavailable
• Methods for interpreting and understanding deep neural networks→Explaining nonlinear classification decisions with deep Taylor decompositionLegacy edge — source detail unavailable
• On hyperparameter optimization of machine learning algorithms: Theory and practice→Algorithms for Hyper-Parameter OptimizationLegacy edge — source detail unavailable
• On hyperparameter optimization of machine learning algorithms: Theory and practice→On Over-fitting in Model Selection and Subsequent Selection Bias in Performance EvaluationLegacy edge — source detail unavailable
• Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Gaussian Processes for Machine LearningLegacy edge — source detail unavailable
• Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→An introduction to kernel-based learning algorithmsLegacy edge — source detail unavailable
• Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Explaining nonlinear classification decisions with deep Taylor decompositionLegacy edge — source detail unavailable
• Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Methods for interpreting and understanding deep neural networksLegacy edge — source detail unavailable