14 citations · 31 across the 3 of their papers we have counts for
3 papers
cs.LG2018★ 5 cited
Dynamic Prediction Length for Time Series with Sequence to Sequence Networks
Mark Harmon, Diego Klabjan
Recurrent neural networks and sequence to sequence models require a predetermined length for prediction output length. Our model addresses this by allowing the network to predict a…
stat.ML2017★ 14 cited
Activation Ensembles for Deep Neural Networks
Mark Harmon, Diego Klabjan
Many activation functions have been proposed in the past, but selecting an adequate one requires trial and error. We propose a new methodology of designing activation functions wit…
stat.ML2016★ 12 cited
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…