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Unsupervised Learning of Video Representations using LSTMs
We use Long Short Term Memory (LSTM) networks to learn representations of video sequences. Our model uses an encoder LSTM to map an input sequence into a fixed length representation. ThisExpand
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Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
In this work, we propose to apply trust region optimization to deep reinforcement learning using a recently proposed Kronecker-factored approximation to the curvature. We extend the framework ofExpand
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Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement
We propose a conditional non-autoregressive neural sequence model based on iterative refinement. The proposed model is designed based on the principles of latent variable models and denoisingExpand
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Generating Images from Captions with Attention
Motivated by the recent progress in generative models, we introduce a model that generates images from natural language descriptions. The proposed model iteratively draws patches on a canvas, whileExpand
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Initialization Strategies of Spatio-Temporal Convolutional Neural Networks
We propose a new way of incorporating temporal information present in videos into Spatial Convolutional Neural Networks (ConvNets) trained on images, that avoids training Spatio-Temporal ConvNetsExpand
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A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models
Undirected neural sequence models such as BERT (Devlin et al., 2019) have received renewed interest due to their success on discriminative natural language understanding tasks such asExpand
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Molecular Geometry Prediction using a Deep Generative Graph Neural Network
A molecule’s geometry, also known as conformation, is one of a molecule’s most important properties, determining the reactions it participates in, the bonds it forms, and the interactions it has withExpand
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Second-order Optimization for Deep Reinforcement Learning using Kronecker-factored Approximation
In this work, we propose to apply trust region optimization to deep reinforcement learning using a recently proposed Kronecker-factored approximation to the curvature. We extend the framework ofExpand
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Finger tracking: facilitating non-commercial content production for mobile e-reading applications
Limited literacy and visual impairment reduce the ability of many to read on their own. Current e-reader solutions rely on either unnatural synthetic voices or professionally produced audio e-books.Expand
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Simple Nearest Neighbor Policy Method for Continuous Control Tasks
We design a new policy, called a nearest neighbor policy, that does not require any optimization for simple, low-dimensional continuous control tasks. As this policy does not require anyExpand
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