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Found 5 papers, 0 papers with code
Time Weaver: A Conditional Time Series Generation Model
Current approaches to time series generation often ignore this paired metadata, and its heterogeneity poses several practical challenges in adapting existing conditional generation approaches from the image, audio, and video domains to the time series domain.
Symbolic Regression on Sparse and Noisy Data with Gaussian Processes
To overcome this, we combine Gaussian process regression with a sparse identification of nonlinear dynamics (SINDy) method to denoise the data and identify nonlinear dynamical equations.
Data Games: A Game-Theoretic Approach to Swarm Robotic Data Collection
Instead, we propose a cooperative data sampling strategy where geo-distributed AVs collaborate to collect a diverse ML training dataset in the cloud.
Robust Forecasting for Robotic Control: A Game-Theoretic Approach
In order to model real-world factors affecting future forecasts, we introduce the notion of an adversary, which perturbs observed historical time series to increase a robot's ultimate control cost.
Imitative Planning using Conditional Normalizing Flow
A popular way to plan trajectories in dynamic urban scenarios for Autonomous Vehicles is to rely on explicitly specified and hand crafted cost functions, coupled with random sampling in the trajectory space to find the minimum cost trajectory.
