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Gated linear contextual bandits
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Domain adaptation for robotic control using self-supervised learning
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Exploration using hypermodels
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Modulating agent behavior to optimize learning progress
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Reinforcement learning using meta-learned intrinsic rewards
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High fidelity speech synthesis with adversarial networks
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Controlling agents using causally correct environment models
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Augmenting attention-based neural networks to selectively attend to past inputs
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Training action selection neural networks using hindsight modelling
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Fast sparse neural networks
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Training action selection neural networks using q-learning combined with look ahead search
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Data-driven robot control
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Gated attention neural networks
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Antisymmetric neural networks
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Training a neural network to control an agent using task-relevant adversarial imitation learning
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Robust reinforcement learning for continuous control with model misspecification
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Hierarchical policies for multitask transfer
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Generative adversarial networks with temporal and spatial discriminators for efficient video generation
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Neural network-based memory system with variable recirculation of queries using memory content
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Jointly learning exploratory and non-exploratory action selection policies
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