Deep Learning: Methods and Applications

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

• Deep learning in neural networks: An overview→Deep Learning: Methods and ApplicationsLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Deep Learning: Methods and ApplicationsLegacy edge — source detail unavailable
• Deep learning and its applications to machine health monitoring→Deep Learning: Methods and ApplicationsLegacy edge — source detail unavailable
• Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Researc…→Deep Learning: Methods and ApplicationsLegacy edge — source detail unavailable
• Ensemble deep learning: A review→Deep Learning: Methods and ApplicationsLegacy edge — source detail unavailable
• Artificial intelligence in digital pathology — new tools for diagnosis and precision onco…→Deep Learning: Methods and ApplicationsLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→A tutorial on hidden Markov models and selected applications in speech recognitionLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Efficient Estimation of Word Representations in Vector SpaceLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Introduction to information retrievalLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Machine learning a probabilistic perspectiveLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Speech recognition with deep recurrent neural networksLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Stacked generalizationLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Recursive Deep Models for Semantic Compositionality Over a Sentiment TreebankLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Improving neural networks by preventing co-adaptation of feature detectorsLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Practical Bayesian Optimization of Machine Learning AlgorithmsLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Connectionist temporal classificationLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Recurrent neural network based language modelLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Deep Sparse Rectifier Neural NetworksLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Natural Language Processing (almost) from ScratchLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→A direct adaptive method for faster backpropagation learning: the RPROP algorithmLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→On the difficulty of training Recurrent Neural NetworksLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Phoneme recognition using time-delay neural networksLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Why Does Unsupervised Pre-training Help Deep Learning?Legacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Learning deep structured semantic models for web search using clickthrough dataLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→DeViSE: A Deep Visual-Semantic Embedding ModelLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Word Representations: A Simple and General Method for Semi-Supervised LearningLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Deep Neural Networks for Acoustic Modeling in Speech RecognitionLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Hybrid speech recognition with Deep Bidirectional LSTMLegacy edge — source detail unavailable
• Understanding the difficulty of training deep feedforward neural networks→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Understanding the difficulty of training deep feedforward neural networks→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Understanding the difficulty of training deep feedforward neural networks→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Understanding the difficulty of training deep feedforward neural networks→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Recurrent neural network based language model→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• On the difficulty of training Recurrent Neural Networks→Long Short-Term MemoryLegacy edge — source detail unavailable
• On the difficulty of training Recurrent Neural Networks→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Improving neural networks by preventing co-adaptation of feature detectors→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Improving neural networks by preventing co-adaptation of feature detectors→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Hybrid speech recognition with Deep Bidirectional LSTM→Long Short-Term MemoryLegacy edge — source detail unavailable
• Hybrid speech recognition with Deep Bidirectional LSTM→Connectionist temporal classificationLegacy edge — source detail unavailable
• Hybrid speech recognition with Deep Bidirectional LSTM→Speech recognition with deep recurrent neural networksLegacy edge — source detail unavailable
• Hybrid speech recognition with Deep Bidirectional LSTM→Deep Neural Networks for Acoustic Modeling in Speech RecognitionLegacy edge — source detail unavailable
• Long Short-Term Memory→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Stacked generalizationLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→On the difficulty of training Recurrent Neural NetworksLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Improving neural networks by preventing co-adaptation of feature detectorsLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Connectionist temporal classificationLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Why Does Unsupervised Pre-training Help Deep Learning?Legacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Speech recognition with deep recurrent neural networksLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→A direct adaptive method for faster backpropagation learning: the RPROP algorithmLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Deep Sparse Rectifier Neural NetworksLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Stacked generalizationLegacy edge — source detail unavailable
• Reducing the Dimensionality of Data with Neural Networks→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• A unified architecture for natural language processing→Phoneme recognition using time-delay neural networksLegacy edge — source detail unavailable
• DeViSE: A Deep Visual-Semantic Embedding Model→Efficient Estimation of Word Representations in Vector SpaceLegacy edge — source detail unavailable
• DeViSE: A Deep Visual-Semantic Embedding Model→Improving neural networks by preventing co-adaptation of feature detectorsLegacy edge — source detail unavailable
• Connectionist temporal classification→Long Short-Term MemoryLegacy edge — source detail unavailable
• Connectionist temporal classification→A tutorial on hidden Markov models and selected applications in speech recognitionLegacy edge — source detail unavailable
• Learning deep structured semantic models for web search using clickthrough data→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Learning deep structured semantic models for web search using clickthrough data→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Learning deep structured semantic models for web search using clickthrough data→Natural Language Processing (almost) from ScratchLegacy edge — source detail unavailable
• Learning deep structured semantic models for web search using clickthrough data→Deep Neural Networks for Acoustic Modeling in Speech RecognitionLegacy edge — source detail unavailable
• Why Does Unsupervised Pre-training Help Deep Learning?→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Why Does Unsupervised Pre-training Help Deep Learning?→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Why Does Unsupervised Pre-training Help Deep Learning?→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Why Does Unsupervised Pre-training Help Deep Learning?→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Speech recognition with deep recurrent neural networks→Long Short-Term MemoryLegacy edge — source detail unavailable
• Speech recognition with deep recurrent neural networks→Connectionist temporal classificationLegacy edge — source detail unavailable
• Speech recognition with deep recurrent neural networks→Deep Neural Networks for Acoustic Modeling in Speech RecognitionLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Why Does Unsupervised Pre-training Help Deep Learning?Legacy edge — source detail unavailable
• Deep Sparse Rectifier Neural Networks→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Sparse Rectifier Neural Networks→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep Sparse Rectifier Neural Networks→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Sparse Rectifier Neural Networks→Why Does Unsupervised Pre-training Help Deep Learning?Legacy edge — source detail unavailable
• Word Representations: A Simple and General Method for Semi-Supervised Learning→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Natural Language Processing (almost) from Scratch→Phoneme recognition using time-delay neural networksLegacy edge — source detail unavailable
• Natural Language Processing (almost) from Scratch→A tutorial on hidden Markov models and selected applications in speech recognitionLegacy edge — source detail unavailable
• Natural Language Processing (almost) from Scratch→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Natural Language Processing (almost) from Scratch→Word Representations: A Simple and General Method for Semi-Supervised LearningLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Improving neural networks by preventing co-adaptation of feature detectorsLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Deep learning in neural networks: An overviewLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Why Does Unsupervised Pre-training Help Deep Learning?Legacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Deep Sparse Rectifier Neural NetworksLegacy edge — source detail unavailable
• Deep learning and its applications to machine health monitoring→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep learning and its applications to machine health monitoring→Deep learning in neural networks: An overviewLegacy edge — source detail unavailable
• Deep learning and its applications to machine health monitoring→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Deep learning and its applications to machine health monitoring→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Artificial intelligence in digital pathology — new tools for diagnosis and precision onco…→Long Short-Term MemoryLegacy edge — source detail unavailable
• Artificial intelligence in digital pathology — new tools for diagnosis and precision onco…→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Ensemble deep learning: A review→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Ensemble deep learning: A review→Stacked generalizationLegacy edge — source detail unavailable
• Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Researc…→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Researc…→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable