19 citations · 87 across the 19 of their papers we have counts for
36 papers
BORE: Bayesian Optimization by Density-Ratio Estimation
Louis C. Tiao, Aaron Klein, Matthias Seeger +3
Bayesian optimization (BO) is among the most effective and widely-used blackbox optimization methods. BO proposes solutions according to an explore-exploit trade-off criterion enco…
A User's Guide to Calibrating Robotics Simulators
Bhairav Mehta, Ankur Handa, Dieter Fox +1
Simulators are a critical component of modern robotics research. Strategies for both perception and decision making can be studied in simulation first before deployed to real world…
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements
Weiming Zhi, Tin Lai, Lionel Ott +1
Critical for the coexistence of humans and robots in dynamic environments is the capability for agents to understand each other's actions, and anticipate their movements. This pape…
STReSSD: Sim-To-Real from Sound for Stochastic Dynamics
Carolyn Matl, Yashraj Narang, Dieter Fox +2
Sound is an information-rich medium that captures dynamic physical events. This work presents STReSSD, a framework that uses sound to bridge the simulation-to-reality gap for stoch…
Fast Uncertainty Quantification for Deep Object Pose Estimation
Guanya Shi, Yifeng Zhu, Jonathan Tremblay +4
Deep learning-based object pose estimators are often unreliable and overconfident especially when the input image is outside the training domain, for instance, with sim2real transf…
Stein Variational Model Predictive Control
Alexander Lambert, Adam Fishman, Dieter Fox +2
Decision making under uncertainty is critical to real-world, autonomous systems. Model Predictive Control (MPC) methods have demonstrated favorable performance in practice, but rem…