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Dynamic Prediction Length for Time Series with Sequence to Sequence Networks
Recurrent neural networks and sequence to sequence models require a predetermined length for prediction output length.
Activation Ensembles for Deep Neural Networks
We propose a new methodology of designing activation functions within a neural network at each layer.
Predicting Shot Making in Basketball Learnt from Adversarial Multiagent Trajectories
In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories.
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