189 citations · 579 across the 11 of their papers we have counts for
6 papers · 1 filter
Technology Readiness Levels for Machine Learning Systems
Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic +12
The development and deployment of machine learning (ML) systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of dilig…
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation
Yukai Liu, Rose Yu, Stephan Zheng +2
Missing value imputation is a fundamental problem in spatiotemporal modeling, from motion tracking to the dynamics of physical systems. Deep autoregressive models suffer from error…
Generating Multi-Agent Trajectories using Programmatic Weak Supervision
Eric Zhan, Stephan Zheng, Yisong Yue +2
We study the problem of training sequential generative models for capturing coordinated multi-agent trajectory behavior, such as offensive basketball gameplay. When modeling such s…
Multi-resolution Tensor Learning for Large-Scale Spatial Data
Stephan Zheng, Rose Yu, Yisong Yue
High-dimensional tensor models are notoriously computationally expensive to train. We present a meta-learning algorithm, MMT, that can significantly speed up the process for spatia…
Long-term Forecasting using Higher Order Tensor RNNs
Rose Yu, Stephan Zheng, Anima Anandkumar +1
We present Higher-Order Tensor RNN (HOT-RNN), a novel family of neural sequence architectures for multivariate forecasting in environments with nonlinear dynamics. Long-term foreca…
Generating Long-term Trajectories Using Deep Hierarchical Networks
Stephan Zheng, Yisong Yue, Patrick Lucey
We study the problem of modeling spatiotemporal trajectories over long time horizons using expert demonstrations. For instance, in sports, agents often choose action sequences with…