1 citations · 2 across the 9 of their papers we have counts for
3 papers · 1 filter
SAVER: A Toolbox for Sampling-Based, Probabilistic Verification of Neural Networks
Vignesh Sivaramakrishnan, Krishna C. Kalagarla, Rosalyn Devonport +3
We present a neural network verification toolbox to 1) assess the probability of satisfaction of a constraint, and 2) synthesize a set expansion factor to achieve the probability o…
DUST: A Framework for Data-Driven Density Steering
Joshua Pilipovsky, Panagiotis Tsiotras
We consider the problem of data-driven stochastic optimal control of an unknown LTI dynamical system. Assuming the process noise is normally distributed, we pose the problem of ste…
Distributionally Robust Density Control with Wasserstein Ambiguity Sets
Joshua Pilipovsky, Panagiotis Tsiotras
Precise control under uncertainty requires a good understanding and characterization of the noise affecting the system. This paper studies the problem of steering state distributio…