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Found 4 papers, 1 papers with code
A Neural Temporal Model for Human Motion Prediction
We propose novel neural temporal models for predicting and synthesizing human motion, achieving state-of-the-art in modeling long-term motion trajectories while being competitive with prior work in short-term prediction and requiring significantly less computation.
Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading
Physical library collections are valuable and long standing resources for knowledge and learning.
A Simple Baseline for Travel Time Estimation using Large-Scale Trip Data
The increased availability of large-scale trajectory data around the world provides rich information for the study of urban dynamics.
Private Posterior distributions from Variational approximations
We focus on estimating posterior distributions of parameters of the naive Bayes log-linear model, where the sufficient statistics of this model are shared using a differentially private interface.
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