Methods for Images, Time Series, and Activation Functions with Deep Neural NetworksPublic Deposited
In this work, we explore the utility of the three main types of neural networks: feed forward, convolutional, and recurrent. While using these networks, we develop a new way to model multiagent trajectory data, explore the use of multiple activation functions for neurons at each layer of a neural network, and create a new model that makes a dynamic number of predictions with sequence data.
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