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Empirical Evaluation of Supervision Signals for Style Transfer Models
In this work we empirically compare the dominant optimization paradigms which provide supervision signals during training: backtranslation, adversarial training and reinforcement learning.
A Framework for Learning Invariant Physical Relations in Multimodal Sensory Processing
We design a novel neural network architecture capable of learning, in an unsupervised manner, relations among multiple sensory cues.
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