UNIFY: Multi-Belief Bayesian Grid Framework based on Automotive Radar. - Stefan Haag; Bharanidhar Duraisamy; Daniel Pfrommer; Wolfgang Koch 001; Martin Fritzsche; Jürgen Dickmann (CoRR, 2021)

TaSIL: Taylor Series Imitation Learning. - Daniel Pfrommer; Thomas T. C. K. Zhang; Stephen Tu; Nikolai Matni (NeurIPS, 2022)

Linear Variational State Space Filtering. - Daniel Pfrommer; Nikolai Matni (CoRR, 2022)

The Power of Learned Locally Linear Models for Nonlinear Policy Optimization. - Daniel Pfrommer; Max Simchowitz; Tyler Westenbroek; Nikolai Matni; Stephen Tu (ICML, 2023)

Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior. - Adam Block; Ali Jadbabaie; Daniel Pfrommer; Max Simchowitz; Russ Tedrake (NeurIPS, 2023)

Smooth Model Predictive Control with Applications to Statistical Learning. - Kwangjun Ahn; Daniel Pfrommer; Jack Umenberger; Tobia Marcucci; Zakaria Mhammedi; Ali Jadbabaie (CoRR, 2023)

Imitating Complex Trajectories: Bridging Low-Level Stability and High-Level Behavior. - Adam Block; Daniel Pfrommer; Max Simchowitz (CoRR, 2023)

On the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control. - Daniel Pfrommer; Swati Padmanabhan; Kwangjun Ahn; Jack Umenberger; Tobia Marcucci; Zakaria Mhammedi; Ali Jadbabaie (CDC, 2024)

Improved Sample Complexity of Imitation Learning for Barrier Model Predictive Control. - Daniel Pfrommer; Swati Padmanabhan; Kwangjun Ahn; Jack Umenberger; Tobia Marcucci; Zakaria Mhammedi; Ali Jadbabaie (CoRR, 2024)

The title of the paper. - Max Simchowitz; Daniel Pfrommer; Ali Jadbabaie (COLT, 2025)

The Pitfalls of Imitation Learning when Actions are Continuous. - Max Simchowitz; Daniel Pfrommer; Ali Jadbabaie (CoRR, 2025)

A Test-Function Approach to Incremental Stability. - Daniel Pfrommer; Max Simchowitz; Ali Jadbabaie (CoRR, 2025)