43 citations · 114 across the 25 of their papers we have counts for
6 papers · 1 filter
PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction
Apoorva Sharma, Sushant Veer, Asher Hancock +3
Inductive Conformal Prediction (ICP) provides a practical and effective approach for equipping deep learning models with uncertainty estimates in the form of set-valued predictions…
MonoNav: MAV Navigation via Monocular Depth Estimation and Reconstruction
Nathaniel Simon, Anirudha Majumdar
A major challenge in deploying the smallest of Micro Aerial Vehicle (MAV) platforms (< 100 g) is their inability to carry sensors that provide high-resolution metric depth informat…
Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners
Allen Z. Ren, Anushri Dixit, Alexandra Bodrova +11
Large language models (LLMs) exhibit a wide range of promising capabilities -- from step-by-step planning to commonsense reasoning -- that may provide utility for robots, but remai…
Online Learning for Obstacle Avoidance
David Snyder, Meghan Booker, Nathaniel Simon +4
We approach the fundamental problem of obstacle avoidance for robotic systems via the lens of online learning. In contrast to prior work that either assumes worst-case realizations…
Fundamental Tradeoffs in Learning with Prior Information
Anirudha Majumdar
We seek to understand fundamental tradeoffs between the accuracy of prior information that a learner has on a given problem and its learning performance. We introduce the notion of…
AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer
Allen Z. Ren, Hongkai Dai, Benjamin Burchfiel +1
Simulation parameter settings such as contact models and object geometry approximations are critical to training robust robotic policies capable of transferring from simulation to…