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Found 10 papers, 7 papers with code
Competition-Level Code Generation with AlphaCode
Programming is a powerful and ubiquitous problem-solving tool.
Ranked #5 on
Code Generation
on APPS
(Interview Pass@1000 metric)
Step-unrolled Denoising Autoencoders for Text Generation
In this paper we propose a new generative model of text, Step-unrolled Denoising Autoencoder (SUNDAE), that does not rely on autoregressive models.
Hierarchical Multiscale Recurrent Neural Networks
Multiscale recurrent neural networks have been considered as a promising approach to resolve this issue, yet there has been a lack of empirical evidence showing that this type of models can actually capture the temporal dependencies by discovering the latent hierarchical structure of the sequence.
Ranked #19 on
Language Modelling
on Text8
A Character-Level Decoder without Explicit Segmentation for Neural Machine Translation
The existing machine translation systems, whether phrase-based or neural, have relied almost exclusively on word-level modelling with explicit segmentation.
Ranked #3 on
Machine Translation
on WMT2015 English-German
Iterative Refinement of the Approximate Posterior for Directed Belief Networks
Variational methods that rely on a recognition network to approximate the posterior of directed graphical models offer better inference and learning than previous methods.
Detecting Interrogative Utterances with Recurrent Neural Networks
In this paper, we explore different neural network architectures that can predict if a speaker of a given utterance is asking a question or making a statement.
A Recurrent Latent Variable Model for Sequential Data
In this paper, we explore the inclusion of latent random variables into the dynamic hidden state of a recurrent neural network (RNN) by combining elements of the variational autoencoder.
Gated Feedback Recurrent Neural Networks
In this work, we propose a novel recurrent neural network (RNN) architecture.
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
In this paper we compare different types of recurrent units in recurrent neural networks (RNNs).
Ranked #10 on
Music Modeling
on JSB Chorales
