10 citations · 22 across the 7 of their papers we have counts for
8 papers
Toward Single-Step MPPI via Differentiable Predictive Control
Viet-Anh Le, Renukanandan Tumu, Rahul Mangharam
Model predictive path integral (MPPI) is a sampling-based method for solving complex model predictive control (MPC) problems, but its real-time implementation is challenged by comp…
AdaptNC: Adaptive Nonconformity Scores for Conformal Prediction under Distribution Shift
Renukanandan Tumu, Aditya Singh, Rahul Mangharam
Rigorous uncertainty quantification is essential for the safe deployment of autonomous systems in unconstrained environments. Conformal Prediction (CP) provides a distribution-free…
Multiagent Social Influence: Modeling Persuasion in Contested Social Networks
Renukanandan Tumu, Cristian Ioan Vasile, Victor Preciado +1
We present the Social Influence Game (SIG), a framework for modeling adversarial persuasion in social networks with an arbitrary number of competing players. Our goal is to provide…
Differentiable Predictive Control for Large-Scale Urban Road Networks
Renukanandan Tumu, Wenceslao Shaw Cortez, Ján Drgoňa +2
Transportation is a major contributor to CO2 emissions, making it essential to optimize traffic networks to reduce energy-related emissions. This paper presents a novel approach to…
Conformal Off-Policy Prediction for Multi-Agent Systems
Tom Kuipers, Renukanandan Tumu, Shuo Yang +3
Off-Policy Prediction (OPP), i.e., predicting the outcomes of a target policy using only data collected under a nominal (behavioural) policy, is a paramount problem in data-driven…
Multi-Modal Conformal Prediction Regions with Simple Structures by Optimizing Convex Shape Templates
Renukanandan Tumu, Matthew Cleaveland, Rahul Mangharam +2
Conformal prediction is a statistical tool for producing prediction regions for machine learning models that are valid with high probability. A key component of conformal predictio…
Physics Constrained Motion Prediction with Uncertainty Quantification
Renukanandan Tumu, Lars Lindemann, Truong Nghiem +1
Predicting the motion of dynamic agents is a critical task for guaranteeing the safety of autonomous systems. A particular challenge is that motion prediction algorithms should obe…
Winning the 3rd Japan Automotive AI Challenge -- Autonomous Racing with the Autoware.Auto Open Source Software Stack
Zirui Zang, Renukanandan Tumu, Johannes Betz +2
The 3rd Japan Automotive AI Challenge was an international online autonomous racing challenge where 164 teams competed in December 2021. This paper outlines the winning strategy to…