Towards Provably Safe Control for Smart Wheelchairs. - Meeko Oishi; Nikolai Matni (AAAI Fall Symposium: AI in Eldercare: New Solutions to Old Problems, 2008)

Reachability-based abstraction for an aircraft landing under shared control. - Nikolai Matni; Meeko Oishi (ACC, 2008)

Reachability analysis for continuous systems under shared control: Application to user-interface design. - Nikolai Matni; Meeko Oishi (CDC, 2009)

Stability of switched block upper-triangular linear systems with switching delay: Application to large distributed systems. - Nikolai Matni; Meeko Oishi (ACC, 2011)

A projection framework for near-potential polynomial games. - Nikolai Matni (CDC, 2012)

A dual problem in ℌ2 decentralized control subject to delays. - Nikolai Matni; John C. Doyle 001 (ACC, 2013)

A heuristic for sub-optimal ℌ2 decentralized control subject to delay in non-quadratically-invariant systems. - Nikolai Matni; John C. Doyle 001 (ACC, 2013)

Reverse engineering combination therapies for evolutionary dynamics of disease: An ℌ∞ approach. - Vanessa Jonsson; Nikolai Matni; Richard M. Murray (CDC, 2013)

Communication delay co-design in ℌ2 decentralized control Using atomic norm minimization. - Nikolai Matni (CDC, 2013)

Optimal distributed LQG state feedback with varying communication delay. - Nikolai Matni; John C. Doyle 001 (CDC, 2013)

A convex approach to consensus on SO(n). - Nikolai Matni; Matanya B. Horowitz (Allerton, 2014)

Localized distributed optimal control with output feedback and communication delays. - Yuh-Shyan Wang; Nikolai Matni (Allerton, 2014)

Localized distributed state feedback control with communication delays. - Yuh Shyang Wang; Nikolai Matni; Seungil You; John C. Doyle 001 (ACC, 2014)

Synthesizing combination therapies for evolutionary dynamics of disease for nonlinear pharmacodynamics. - Vanessa Jonsson; Nikolai Matni; Richard M. Murray (CDC, 2014)

Distributed control subject to delays satisfying an ℋ1 norm bound. - Nikolai Matni (CDC, 2014)

Localized LQR optimal control. - Yuh Shyang Wang; Nikolai Matni; John C. Doyle 001 (CDC, 2014)

Resilience in Large Scale Distributed Systems. - Nikolai Matni; Yoke Peng Leong; Yuh Shyang Wang; Seungil You; Matanya B. Horowitz; John C. Doyle 001 (CSER, 2014)

Convex relaxations of SE(2) and SE(3) for visual pose estimation. - Matanya B. Horowitz; Nikolai Matni; Joel W. Burdick (ICRA, 2014)

Communication Delay Co-Design in $ mathcal{H}_2$ Distributed Control Using Atomic Norm Minimization. - Nikolai Matni (CoRR, 2014)

Optimal Two Player LQR State Feedback With Varying Delay. - Nikolai Matni; Andrew G. Lamperski; John C. Doyle 001 (CoRR, 2014)

Low-Rank and Low-Order Decompositions for Local System Identification. - Nikolai Matni; Anders Rantzer (CoRR, 2014)

Hard limits on robust control over delayed and quantized communication channels with applications to sensorimotor control. - Yorie Nakahira; Nikolai Matni; John C. Doyle 001 (CDC, 2015)

A convex approach to sparse ℋ∞ analysis & synthesis. - Seungil You; Nikolai Matni (CDC, 2015)

A case study in network architecture tradeoffs. - Nikolai Matni; Ao Tang; John C. Doyle 001 (SOSR, 2015)

A Convex Approach to Sparse H infinity Analysis & Synthesis. - Seungil You; Nikolai Matni (CoRR, 2015)

A Theory of dynamics, control and optimization in layered architectures. - Nikolai Matni; John C. Doyle 001 (ACC, 2016)

Localized LQG optimal control for large-scale systems. - Yuh Shyang Wang; Nikolai Matni (ACC, 2016)

Localized LQR control with actuator regularization. - Yuh Shyang Wang; Nikolai Matni; John C. Doyle 001 (ACC, 2016)

Teaching control theory in high school. - John Doyle 001; Yorie Nakahira; Yoke Peng Leong; Emily Jenson; Adam Dai; Dimitar Ho; Nikolai Matni (CDC, 2016)

A System Level Approach to Controller Synthesis. - Yuh Shyang Wang; Nikolai Matni; John C. Doyle 001 (CoRR, 2016)

Regularization for Design. - Nikolai Matni; Venkat Chandrasekaran (IEEE Trans. Autom. Control., 2016)

Structured state space realizations for SLS distributed controllers. - James Anderson 001; Nikolai Matni (Allerton, 2017)

Optimal zero-queue congestion control using ADMM. - Nikolai Matni (ACC, 2017)

System Level Parameterizations, constraints and synthesis. - Yuh Shyang Wang; Nikolai Matni; John C. Doyle 001 (ACC, 2017)

System level synthesis: A tutorial. - John C. Doyle 001; Nikolai Matni; Yuh Shyang Wang; James Anderson 001; Steven H. Low (CDC, 2017)

Scalable system level synthesis for virtually localizable systems. - Nikolai Matni; Yuh-Shyang Wang; James Anderson 001 (CDC, 2017)

HFTraC: High-Frequency Traffic Control. - Ning Wu; Yingjie Bi; Nithin Michael; Ao Tang; John Doyle 001; Nikolai Matni (SIGMETRICS (Abstracts), 2017)

Separable and Localized System Level Synthesis for Large-Scale Systems. - Yuh Shyang Wang; Nikolai Matni; John C. Doyle 001 (CoRR, 2017)

Communication Delay Co-Design in ℋ2-Distributed Control Using Atomic Norm Minimization. - Nikolai Matni (IEEE Trans. Control. Netw. Syst., 2017)

Passive-Aggressive Learning and Control. - Dimitar Ho; Nikolai Matni; John C. Doyle 001 (ACC, 2018)

Finite-Data Performance Guarantees for the Output-Feedback Control of an Unknown System. - Ross Boczar; Nikolai Matni; Benjamin Recht (CDC, 2018)

Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator. - Sarah Dean; Horia Mania; Nikolai Matni; Benjamin Recht; Stephen Tu (NeurIPS, 2018)

Separable and Localized System-Level Synthesis for Large-Scale Systems. - Yuh-Shyang Wang; Nikolai Matni; John C. Doyle 001 (IEEE Trans. Autom. Control., 2018)

A Control-Theoretic Approach to In-Network Congestion Management. - Ning Wu; Yingjie Bi; Nithin Michael; Ao Tang; John C. Doyle 001; Nikolai Matni (IEEE/ACM Trans. Netw., 2018)

Safely Learning to Control the Constrained Linear Quadratic Regulator. - Sarah Dean; Stephen Tu; Nikolai Matni; Benjamin Recht (ACC, 2019)

Learning Sparse Dynamical Systems from a Single Sample Trajectory. - Salar Fattahi; Nikolai Matni; Somayeh Sojoudi (CDC, 2019)

From self-tuning regulators to reinforcement learning and back again. - Nikolai Matni; Alexandre Proutière; Anders Rantzer; Stephen Tu (CDC, 2019)

A Tutorial on Concentration Bounds for System Identification. - Nikolai Matni; Stephen Tu (CDC, 2019)

System level synthesis. - James Anderson 001; John C. Doyle 001; Steven H. Low; Nikolai Matni (Annu. Rev. Control., 2019)

Sparsity Preserving Discretization With Error Bounds. - James Anderson 001; Nikolai Matni; Yuxiao Chen 001 (CoRR, 2019)

Efficient Learning of Distributed Linear-Quadratic Controllers. - Salar Fattahi; Nikolai Matni; Somayeh Sojoudi (CoRR, 2019)

Distributed and Localized Model Predictive Control via System Level Synthesis. - Carmen Amo Alonso; Nikolai Matni (CoRR, 2019)

A System-Level Approach to Controller Synthesis. - Yuh-Shyang Wang; Nikolai Matni; John C. Doyle 001 (IEEE Trans. Autom. Control., 2019)

The driver and the engineer: Reinforcement learning and robust control. - Natalie Bernat; Jiexin Chen; Nikolai Matni; John Doyle 001 (ACC, 2020)

Robust Performance Guarantees for System Level Synthesis. - Nikolai Matni; Anish A. Sarma (ACC, 2020)

Explicit Distributed and Localized Model Predictive Control via System Level Synthesis. - Carmen Amo Alonso; Nikolai Matni; James Anderson 001 (CDC, 2020)

Distributed and Localized Closed Loop Model Predictive Control via System Level Synthesis. - Carmen Amo Alonso; Nikolai Matni (CDC, 2020)

Robust Closed-loop Model Predictive Control via System Level Synthesis. - Shaoru Chen; Han Wang 016; Manfred Morari; Victor M. Preciado; Nikolai Matni (CDC, 2020)

Learning Control Barrier Functions from Expert Demonstrations. - Alexander Robey; Haimin Hu; Lars Lindemann; Hanwen Zhang; Dimos V. Dimarogonas; Stephen Tu; Nikolai Matni (CDC, 2020)

Learning Stability Certificates from Data. - Nicholas M. Boffi; Stephen Tu; Nikolai Matni; Jean-Jacques E. Slotine; Vikas Sindhwani (CoRL, 2020)

Learning Hybrid Control Barrier Functions from Data. - Lars Lindemann; Haimin Hu; Alexander Robey; Hanwen Zhang; Dimos V. Dimarogonas; Stephen Tu; Nikolai Matni (CoRL, 2020)

PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction. - Sangdon Park 001; Osbert Bastani; Nikolai Matni; Insup Lee 001 (ICLR, 2020)

Robust, Perception Based Control with Quadrotors. - Laura Jarin-Lipschitz; Rebecca Li; Ty Nguyen; Vijay Kumar 001; Nikolai Matni (IROS, 2020)

Robust Guarantees for Perception-Based Control. - Sarah Dean; Nikolai Matni; Benjamin Recht; Vickie Ye (L4DC, 2020)

Sample Complexity of Kalman Filtering for Unknown Systems. - Anastasios Tsiamis; Nikolai Matni; George J. Pappas (L4DC, 2020)

Action for Better Prediction. - Bernadette Bucher; Karl Schmeckpeper; Nikolai Matni; Kostas Daniilidis (CoRR, 2020)

Evaluating Robust, Perception Based Control with Quadrotors. - Laura Jarin-Lipschitz; Rebecca Li; Ty Nguyen; Vijay Kumar 001; Nikolai Matni (CoRR, 2020)

On the Sample Complexity of the Linear Quadratic Regulator. - Sarah Dean; Horia Mania; Nikolai Matni; Benjamin Recht; Stephen Tu (Found. Comput. Math., 2020)

Efficient Learning of Distributed Linear-Quadratic Control Policies. - Salar Fattahi; Nikolai Matni; Somayeh Sojoudi (SIAM J. Control. Optim., 2020)

Learning Robust Hybrid Control Barrier Functions for Uncertain Systems. - Alexander Robey; Lars Lindemann; Stephen Tu; Nikolai Matni (ADHS, 2021)

STL Robustness Risk over Discrete-Time Stochastic Processes. - Lars Lindemann; Nikolai Matni; George J. Pappas (CDC, 2021)

Communication Topology Co-Design in Graph Recurrent Neural Network based Distributed Control. - Fengjun Yang; Nikolai Matni (CDC, 2021)

An Adversarial Objective for Scalable Exploration. - Bernadette Bucher; Karl Schmeckpeper; Nikolai Matni; Kostas Daniilidis (IROS, 2021)

How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control? - Jingxi Xu 002; Bruce D. Lee; Nikolai Matni; Dinesh Jayaraman (L4DC, 2021)

Data-Driven System Level Synthesis. - Anton Xue; Nikolai Matni (L4DC, 2021)

Closing the Closed-Loop Distribution Shift in Safe Imitation Learning. - Stephen Tu; Alexander Robey; Nikolai Matni (CoRR, 2021)

System Level Synthesis-based Robust Model Predictive Control through Convex Inner Approximation. - Shaoru Chen; Nikolai Matni; Manfred Morari; Victor M. Preciado (CoRR, 2021)

Adversarial Tradeoffs in Linear Inverse Problems and Robust State Estimation. - Bruce D. Lee; Thomas T. C. K. Zhang; Hamed Hassani; Nikolai Matni (CoRR, 2021)

Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations. - Lars Lindemann; Alexander Robey; Lejun Jiang; Stephen Tu; Nikolai Matni (CoRR, 2021)

Data-driven Distributed and Localized Model Predictive Control. - Carmen Amo Alonso; Fengjun Yang; Nikolai Matni (CoRR, 2021)

Robust Model Predictive Control of Time-Delay Systems through System Level Synthesis. - Shaoru Chen; Ning-Yuan Li 001; Victor M. Preciado; Nikolai Matni (CDC, 2022)

Performance-Robustness Tradeoffs in Adversarially Robust Linear-Quadratic Control. - Bruce D. Lee; Thomas T. C. K. Zhang; Hamed Hassani; Nikolai Matni (CDC, 2022)

Distributed Optimal Control of Graph Symmetric Systems via Graph Filters. - Fengjun Yang; Fernando Gama; Somayeh Sojoudi; Nikolai Matni (CDC, 2022)

How are policy gradient methods affected by the limits of control? - Ingvar M. Ziemann; Anastasios Tsiamis; Henrik Sandberg; Nikolai Matni (CDC, 2022)

Learning to Control Linear Systems can be Hard. - Anastasios Tsiamis; Ingvar M. Ziemann; Manfred Morari; Nikolai Matni; George J. Pappas (COLT, 2022)

Single Trajectory Nonparametric Learning of Nonlinear Dynamics. - Ingvar M. Ziemann; Henrik Sandberg; Nikolai Matni (COLT, 2022)

Uncertainty-driven Planner for Exploration and Navigation. - Georgios Georgakis; Bernadette Bucher; Anton Arapin; Karl Schmeckpeper; Nikolai Matni; Kostas Daniilidis (ICRA, 2022)

Generalization Bounded Implicit Learning of Nearly Discontinuous Functions. - Bibit Bianchini; Mathew Halm; Nikolai Matni; Michael Posa (L4DC, 2022)

On the Sample Complexity of Stability Constrained Imitation Learning. - Stephen Tu; Alexander Robey; Tingnan Zhang; Nikolai Matni (L4DC, 2022)

Adversarially Robust Stability Certificates can be Sample-Efficient. - Thomas T. C. K. Zhang; Stephen Tu; Nicholas M. Boffi; Jean-Jacques E. Slotine; Nikolai Matni (L4DC, 2022)

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)

Statistical Learning Theory for Control: A Finite Sample Perspective. - Anastasios Tsiamis; Ingvar M. Ziemann; Nikolai Matni; George J. Pappas (CoRR, 2022)

Adversarial Tradeoffs in Robust State Estimation. - Thomas T. C. K. Zhang; Bruce D. Lee; Hamed Hassani; Nikolai Matni (ACC, 2023)

Safety Filter Design for Neural Network Systems via Convex Optimization. - Shaoru Chen; Kong Yao Chee; Nikolai Matni; M. Ani Hsieh; George J. Pappas (CDC, 2023)

The Fundamental Limitations of Learning Linear-Quadratic Regulators. - Bruce D. Lee; Ingvar M. Ziemann; Anastasios Tsiamis; Henrik Sandberg; Nikolai Matni (CDC, 2023)

A Tutorial on the Non-Asymptotic Theory of System Identification. - Ingvar M. Ziemann; Anastasios Tsiamis; Bruce D. Lee; Yassir Jedra; Nikolai Matni; George J. Pappas (CDC, 2023)

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

Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning. - David Brandfonbrener; Stephen Tu; Avi Singh; Stefan Welker; Chad Boodoo; Nikolai Matni; Jake Varley (ICRA, 2023)

A Data-Driven Approach to Synthesizing Dynamics-Aware Trajectories for Underactuated Robotic Systems. - Anusha Srikanthan; Fengjun Yang; Igor Spasojevic; Dinesh Thakur; Vijay Kumar 001; Nikolai Matni (IROS, 2023)

Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles. - Kong Yao Chee; M. Ani Hsieh; Nikolai Matni (L4DC, 2023)

Multi-Task Imitation Learning for Linear Dynamical Systems. - Thomas T. C. K. Zhang; Katie Kang; Bruce D. Lee; Claire J. Tomlin; Sergey Levine; Stephen Tu; Nikolai Matni (L4DC, 2023)

The noise level in linear regression with dependent data. - Ingvar M. Ziemann; Stephen Tu; George J. Pappas; Nikolai Matni (NeurIPS, 2023)

Toward Certified Robustness Against Real-World Distribution Shifts. - Haoze Wu 001; Teruhiro Tagomori; Alexander Robey; Fengjun Yang; Nikolai Matni; George J. Pappas; Hamed Hassani; Corina S. Pasareanu; Clark W. Barrett (SaTML, 2023)

Learning Safe and Stable Motion Plans with Neural Ordinary Differential Equations. - Farhad Nawaz; Tianyu Li; Nikolai Matni; Nadia Figueroa (CoRR, 2023)

Meta-Learning Operators to Optimality from Multi-Task Non-IID Data. - Thomas T. C. K. Zhang; Leonardo Felipe Toso; James Anderson 001; Nikolai Matni (CoRR, 2023)

Augmented Lagrangian Methods as Layered Control Architectures. - Anusha Srikanthan; Vijay Kumar 001; Nikolai Matni (CoRR, 2023)

Risk of Stochastic Systems for Temporal Logic Specifications. - Lars Lindemann; Lejun Jiang; Nikolai Matni; George J. Pappas (ACM Trans. Embed. Comput. Syst., 2023)

Distributed and Localized Model-Predictive Control-Part I: Synthesis and Implementation. - Carmen Amo Alonso; Jing Shuang Li; James Anderson 001; Nikolai Matni (IEEE Trans. Control. Netw. Syst., 2023)

Distributed and Localized Model Predictive Control - Part II: Theoretical Guarantees. - Carmen Amo Alonso; Jing Shuang Li; Nikolai Matni; James Anderson 001 (IEEE Trans. Control. Netw. Syst., 2023)

Single Trajectory Conformal Prediction. - Brian Lee; Nikolai Matni (CDC, 2024)

Active Learning for Control-Oriented Identification of Nonlinear Systems. - Bruce D. Lee; Ingvar M. Ziemann; George J. Pappas; Nikolai Matni (CDC, 2024)

Moving Average Estimation by Geometric Optimization. - Alex Nguyen-Le; Nikolai Matni (CDC, 2024)

Coordinating Planning and Tracking in Layered Control Policies via Actor-Critic Learning. - Fengjun Yang; Nikolai Matni (CDC, 2024)

Monocular Event-Based Vision for Obstacle Avoidance with a Quadrotor. - Anish Bhattacharya; Marco Cannici; Nishanth Rao; Yuezhan Tao; Vijay Kumar 001; Nikolai Matni; Davide Scaramuzza 001 (CoRL, 2024)

Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data. - Thomas T. C. K. Zhang; Leonardo Felipe Toso; James Anderson 001; Nikolai Matni (ICLR, 2024)

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples. - Thomas T. C. K. Zhang; Bruce D. Lee; Ingvar M. Ziemann; George J. Pappas; Nikolai Matni (ICML, 2024)

Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss. - Ingvar M. Ziemann; Stephen Tu; George J. Pappas; Nikolai Matni (ICML, 2024)

Learning Complex Motion Plans using Neural ODEs with Safety and Stability Guarantees. - Farhad Nawaz; Tianyu Li; Nikolai Matni; Nadia Figueroa (ICRA, 2024)

Reactive Temporal Logic-based Planning and Control for Interactive Robotic Tasks. - Farhad Nawaz; Shaoting Peng; Lars Lindemann; Nadia Figueroa; Nikolai Matni (IROS, 2024)

Uncertainty-Aware Deployment of Pre-trained Language-Conditioned Imitation Learning Policies. - Bo Wu; Bruce D. Lee; Kostas Daniilidis; Bernadette Bucher; Nikolai Matni (IROS, 2024)

Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification. - Bruce D. Lee; Anders Rantzer; Nikolai Matni (L4DC, 2024)

EvDNeRF: Reconstructing Event Data with Dynamic Neural Radiance Fields. - Anish Bhattacharya; Ratnesh Madaan; Fernando Cladera Ojeda; Sai Vemprala; Rogerio Bonatti; Kostas Daniilidis; Ashish Kapoor; Vijay Kumar 001; Nikolai Matni; Jayesh K. Gupta (WACV, 2024)

Robust model predictive control with polytopic model uncertainty through System Level Synthesis. - Shaoru Chen; Victor M. Preciado; Manfred Morari; Nikolai Matni (Autom., 2024)

Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systems. - Hanli Zhang; Anusha Srikanthan; Spencer Folk; Vijay Kumar 001; Nikolai Matni (CoRR, 2024)

Towards a Theory of Control Architecture: A quantitative framework for layered multi-rate control. - Nikolai Matni; Aaron D. Ames; John C. Doyle 001 (CoRR, 2024)

Vision Transformers for End-to-End Vision-Based Quadrotor Obstacle Avoidance. - Anish Bhattacharya; Nishanth Rao; Dhruv Parikh; Pratik Kunapuli; Nikolai Matni; Vijay Kumar 001 (CoRR, 2024)

Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control. - Bruce D. Lee; Leonardo F. Toso; Thomas T. C. K. Zhang; James Anderson 001; Nikolai Matni (CoRR, 2024)

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples. - Thomas T. Zhang; Bruce D. Lee; Ingvar M. Ziemann; George J. Pappas; Nikolai Matni (CoRR, 2024)

Closed-Loop Analysis of ADMM-Based Suboptimal Linear Model Predictive Control. - Anusha Srikanthan; Aren Karapetyan; Vijay Kumar 001; Nikolai Matni (IEEE Control. Syst. Lett., 2024)

Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control. - Bruce D. Lee; Leonardo F. Toso; Thomas T. Zhang; James Anderson 001; Nikolai Matni (AAAI, 2025)

Domain Randomization is Sample Efficient for Linear Quadratic Control. - Tesshu Fujinami; Bruce D. Lee; Nikolai Matni; George J. Pappas (L4DC, 2025)

Logarithmic Regret for Nonlinear Control. - James Wang; Bruce D. Lee; Ingvar M. Ziemann; Nikolai Matni (L4DC, 2025)

State space models, emergence, and ergodicity: How many parameters are needed for stable predictions? - Ingvar M. Ziemann; Nikolai Matni; George J. Pappas (L4DC, 2025)

On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning. - Thomas T. Zhang; Behrad Moniri; Ansh Nagwekar; Faraz Rahman; Anton Xue; Hamed Hassani; Nikolai Matni (CoRR, 2025)

ADMM-MCBF-LCA: A Layered Control Architecture for Safe Real-Time Navigation. - Anusha Srikanthan; Yifan Xue; Vijay Kumar 001; Nikolai Matni; Nadia Figueroa (CoRR, 2025)

Policy Gradient for LQR with Domain Randomization. - Tesshu Fujinami; Bruce D. Lee; Nikolai Matni; George J. Pappas (CoRR, 2025)

Learning with Imperfect Models: When Multi-step Prediction Mitigates Compounding Error. - Anne Somalwar; Bruce D. Lee; George J. Pappas; Nikolai Matni (CoRR, 2025)

Learning Flatness-Preserving Residuals for Pure-Feedback Systems. - Fengjun Yang; Jake Welde; Nikolai Matni (CoRR, 2025)

Graph-based Path Planning with Dynamic Obstacle Avoidance for Autonomous Parking. - Farhad Nawaz; Minjun Sung; Darshan Gadginmath; Jovin D'sa; Sangjae Bae; David Isele; Nadia Figueroa; Nikolai Matni; Faizan M. Tariq (CoRR, 2025)

Quad-LCD: Layered Control Decomposition Enables Actuator-Feasible Quadrotor Trajectory Planning. - Anusha Srikanthan; Hanli Zhang; Spencer Folk; Vijay Kumar 001; Nikolai Matni (CoRR, 2025)

Performance-Robustness Tradeoffs in Adversarially Robust Control and Estimation. - Bruce D. Lee; Thomas T. C. K. Zhang; Hamed Hassani; Nikolai Matni (IEEE Trans. Autom. Control., 2025)