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Found 4 papers, 1 papers with code
Benchmarking Data Efficiency and Computational Efficiency of Temporal Action Localization Models
This work explores and measures how current deep temporal action localization models perform in settings constrained by the amount of data or computational power.
Investigation of Architectures and Receptive Fields for Appearance-based Gaze Estimation
With the rapid development of deep learning technology in the past decade, appearance-based gaze estimation has attracted great attention from both computer vision and human-computer interaction research communities.
A Deep Learning Approach to Predicting Ventilator Parameters for Mechanically Ventilated Septic Patients
We develop a deep learning approach to predicting a set of ventilator parameters for a mechanically ventilated septic patient using a long and short term memory (LSTM) recurrent neural network (RNN) model.
Optimal Market Making in the Presence of Latency
This paper studies optimal market making for large-tick assets in the presence of latency.
