12 citations · 14 across the 3 of their papers we have counts for
3 papers
Autoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification
Stephanie Ger, Yegna Subramanian Jambunath, Diego Klabjan
Generative Adversarial Networks (GANs) have been used in many different applications to generate realistic synthetic data. We introduce a novel GAN with Autoencoder (GAN-AE) archit…
Layer Flexible Adaptive Computational Time
Lida Zhang, Abdolghani Ebrahimi, Diego Klabjan
Deep recurrent neural networks perform well on sequence data and are the model of choice. However, it is a daunting task to decide the structure of the networks, i.e. the number of…
Predicting Shot Making in Basketball Learnt from Adversarial Multiagent Trajectories
Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey +1
In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting featu…