An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
Shaojie Bai, J. Zico Kolter, Vladlen Koltun
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- Transformer-XL: Attentive Language Models beyond a Fixed-Length Context→An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…Legacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Dropout: a simple way to prevent neural networks from overfittingLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Bidirectional recurrent neural networksLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Building a Large Annotated Corpus of English: The Penn TreebankLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→A unified architecture for natural language processingLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Natural Language Processing (almost) from ScratchLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Backpropagation through time: what it does and how to do itLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Sequence to Sequence Learning with Neural NetworksLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Phoneme recognition using time-delay neural networksLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Parallel Networks that Learn to Pronounce English TextLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→Connectionist learning proceduresLegacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→An Empirical Exploration of Recurrent Network ArchitecturesLegacy edge — source detail unavailable
- A unified architecture for natural language processing→Phoneme recognition using time-delay neural networksLegacy edge — source detail unavailable
- Phoneme recognition using time-delay neural networks→Connectionist learning proceduresLegacy edge — source detail unavailable
- Bidirectional recurrent neural networks→Phoneme recognition using time-delay neural networksLegacy edge — source detail unavailable
- Natural Language Processing (almost) from Scratch→Phoneme recognition using time-delay neural networksLegacy edge — source detail unavailable
- Sequence to Sequence Learning with Neural Networks→Backpropagation through time: what it does and how to do itLegacy edge — source detail unavailable
- Connectionist learning procedures→Parallel Networks that Learn to Pronounce English TextLegacy edge — source detail unavailable
- Connectionist learning procedures→Phoneme recognition using time-delay neural networksLegacy edge — source detail unavailable
- An Empirical Exploration of Recurrent Network Architectures→Building a Large Annotated Corpus of English: The Penn TreebankLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Transformer-XL: Attentive Language Models beyond a Fixed-Length Context | 2019 | 3,202 |
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Topics
| Topic Modeling | Computer Science |
| Natural Language Processing Techniques | Computer Science |
| Music and Audio Processing | Computer Science |
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