Loudmouth: : modifying text-to-speech synthesis in noise. - Rupal Patel; Michael Everett; Eldar Sadikov (ASSETS, 2006)

A Passive Approach to Autonomous Collision Detection and Avoidance. - Plamen Angelov 001; Cosmin Danut Bocaniala; Costas S. Xydeas; Charles Patchett; Darren Ansell; Michael Everett; Gang Leng (UKSim, 2008)

A community college blended learning classroom experience through Artificial Intelligence in Games. - Titus Barik; Michael Everett; Rogelio Enrique Cardona-Rivera; David L. Roberts 001; Edward F. Gehringer (FIE, 2013)

Seeing around corners with a mobile phone?: synthetic aperture audio imaging. - Hisham Bedri; Micha Feigin; Michael Everett; Ivan Filho; Gregory L. Charvat; Ramesh Raskar (SIGGRAPH Posters, 2014)

Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning. - Yu Fan Chen; Miao Liu 001; Michael Everett; Jonathan P. How (ICRA, 2017)

Scalable accelerated decentralized multi-robot policy search in continuous observation spaces. - Shayegan Omidshafiei; Christopher Amato; Miao Liu 001; Michael Everett; Jonathan P. How; John Vian (ICRA, 2017)

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. - Shayegan Omidshafiei; Shih-Yuan Liu; Michael Everett; Brett T. Lopez; Christopher Amato; Miao Liu 001; Jonathan P. How; John Vian (ICRA, 2017)

Socially aware motion planning with deep reinforcement learning. - Yu Fan Chen; Michael Everett; Miao Liu 001; Jonathan P. How (IROS, 2017)

Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning. - Michael Everett; Yu Fan Chen; Jonathan P. How (IROS, 2018)

Three-Dimensional UAV Routing With Deconfliction. - Sohail Razzaq; Costas Xydeas; Michael Everett; Anzar Mahmood; Thamer Alquthami (IEEE Access, 2018)

Certified Adversarial Robustness for Deep Reinforcement Learning. - Björn Lütjens; Michael Everett; Jonathan P. How (CoRL, 2019)

Safe Reinforcement Learning With Model Uncertainty Estimates. - Björn Lütjens; Michael Everett; Jonathan P. How (ICRA, 2019)

Planning Beyond The Sensing Horizon Using a Learned Context. - Michael Everett; Justin Miller; Jonathan P. How (IROS, 2019)

FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments. - Jesus Tordesillas; Brett T. Lopez; Michael Everett; Jonathan P. How (CoRR, 2020)

R-MADDPG for Partially Observable Environments and Limited Communication. - Rose E. Wang; Michael Everett; Jonathan P. How (CoRR, 2020)

Robustness Analysis of Neural Networks via Efficient Partitioning: Theory and Applications in Control Systems. - Michael Everett; Golnaz Habibi; Jonathan P. How (CoRR, 2020)

Multi-Agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning. - Samaneh Hosseini Semnani; Hugh Liu 001; Michael Everett; Anton H. J. de Ruiter; Jonathan P. How (IEEE Robotics Autom. Lett., 2020)

Neural Network Verification in Control. - Michael Everett (CDC, 2021)

Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers. - Michael Everett; Golnaz Habibi; Jonathan P. How (ICRA, 2021)

Collision Avoidance in Pedestrian-Rich Environments With Deep Reinforcement Learning. - Michael Everett; Yu Fan Chen; Jonathan P. How (IEEE Access, 2021)

Reachability Analysis of Neural Feedback Loops. - Michael Everett; Golnaz Habibi; Chuangchuang Sun; Jonathan P. How (IEEE Access, 2021)

Where to go next: Learning a Subgoal Recommendation Policy for Navigation Among Pedestrians. - Bruno Brito; Michael Everett; Jonathan P. How; Javier Alonso-Mora (CoRR, 2021)

Robustness Analysis of Neural Networks via Efficient Partitioning With Applications in Control Systems. - Michael Everett; Golnaz Habibi; Jonathan P. How (IEEE Control. Syst. Lett., 2021)

Where to go Next: Learning a Subgoal Recommendation Policy for Navigation in Dynamic Environments. - Bruno Brito; Michael Everett; Jonathan P. How; Javier Alonso-Mora (IEEE Robotics Autom. Lett., 2021)

Backward Reachability Analysis for Neural Feedback Loops. - Nicholas Rober; Michael Everett; Jonathan P. How (CDC, 2022)

Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC. - Andrea Tagliabue; Dong-Ki Kim; Michael Everett; Jonathan P. How (ICRA, 2022)

Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map. - Xiaoyi Cai; Michael Everett; Jonathan Fink; Jonathan P. How (IROS, 2022)

Influencing Long-Term Behavior in Multiagent Reinforcement Learning. - Dong-Ki Kim; Matthew Riemer; Miao Liu 001; Jakob N. Foerster; Michael Everett; Chuangchuang Sun; Gerald Tesauro; Jonathan P. How (NeurIPS, 2022)

Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems. - Nicholas Rober; Sydney M. Katz; Chelsea Sidrane; Esen Yel; Michael Everett; Mykel J. Kochenderfer; Jonathan P. How (CoRR, 2022)

Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning. - Michael Everett; Björn Lütjens; Jonathan P. How (IEEE Trans. Neural Networks Learn. Syst., 2022)

FASTER: Fast and Safe Trajectory Planner for Navigation in Unknown Environments. - Jesus Tordesillas; Brett T. Lopez; Michael Everett; Jonathan P. How (IEEE Trans. Robotics, 2022)

A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops. - Nicholas Rober; Michael Everett; Songan Zhang; Jonathan P. How (ACC, 2023)

RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot Navigation. - Lakshay Sharma; Michael Everett; Donggun Lee; Xiaoyi Cai; Philip R. Osteen; Jonathan P. How (ICRA, 2023)

Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road Environments. - Xiaoyi Cai; Michael Everett; Lakshay Sharma; Philip R. Osteen; Jonathan P. How (IROS, 2023)

Principles and Guidelines for Evaluating Social Robot Navigation Algorithms. - Anthony G. Francis; Claudia Pérez-D'Arpino; Chengshu Li 001; Fei Xia 002; Alexandre Alahi; Rachid Alami 001; Aniket Bera; Abhijat Biswas; Joydeep Biswas; Rohan Chandra; Hao-Tien Lewis Chiang; Michael Everett; et al. (CoRR, 2023)

Robust Survival Analysis with Adversarial Regularization. - Michael Potter; Stefano Maxenti; Michael Everett (CoRR, 2023)

DRIP: Domain Refinement Iteration With Polytopes for Backward Reachability Analysis of Neural Feedback Loops. - Michael Everett; Rudy Bunel; Shayegan Omidshafiei (IEEE Control. Syst. Lett., 2023)

LiDAR Inertial Odometry And Mapping Using Learned Registration-Relevant Features. - Zihao Dong; Jeff Pflueger; Leonard Jung; David Thorne; Philip R. Osteen; Christa S. Robison; Brett T. Lopez; Michael Everett (CoRR, 2024)

Collision Avoidance Verification of Multiagent Systems With Learned Policies. - Zihao Dong; Shayegan Omidshafiei; Michael Everett (IEEE Control. Syst. Lett., 2024)

EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy. - Xiaoyi Cai; Siddharth Ancha; Lakshay Sharma; Philip R. Osteen; Bernadette Bucher; Stephen Phillips; Jiuguang Wang; Michael Everett; Nicholas Roy; Jonathan P. How (IEEE Trans. Robotics, 2024)

Survival Analysis with Adversarial Regularization. - Michael Potter; Stefano Maxenti; Michael Everett (ICHI, 2025)

Contingency Constrained Planning with MPPI within MPPI. - Leonard Jung; Alexander Estornell; Michael Everett (L4DC, 2025)

Active Learning For Repairable Hardware Systems With Partial Coverage. - Michael Potter; Beyza Kalkanli; Deniz Erdogmus; Michael Everett (CoRR, 2025)

Learning Verifiable Control Policies Using Relaxed Verification. - Puja Chaudhury; Alexander Estornell; Michael Everett (CoRR, 2025)

A Hybrid Framework for Efficient Koopman Operator Learning. - Alexander Estornell; Leonard Jung; Alenna Spiro; Mario Sznaier; Michael Everett (CoRR, 2025)

Learning Smooth State-Dependent Traversability from Dense Point Clouds. - Zihao Dong; Alan Papalia; Leonard Jung; Alenna Spiro; Philip R. Osteen; Christa S. Robison; Michael Everett (CoRR, 2025)

Continuously Optimizing Radar Placement With Model-Predictive Path Integrals. - Michael Potter; Shuo Tang; Paul Ghanem; Milica Stojanovic; Pau Closas; Murat Akçakaya; Ben Wright; Marius Necsoiu; Deniz Erdogmus; Michael Everett; Tales Imbiriba (IEEE Trans. Aerosp. Electron. Syst., 2025)

Principles and Guidelines for Evaluating Social Robot Navigation Algorithms. - Anthony G. Francis; Claudia Pérez-D'Arpino; Chengshu Li 002; Fei Xia 002; Alexandre Alahi; Rachid Alami 001; Aniket Bera; Abhijat Biswas; Joydeep Biswas; Rohan Chandra; Hao-Tien Lewis Chiang; Michael Everett; et al. (ACM Trans. Hum. Robot Interact., 2025)

Verification of Visual Controllers via Compositional Geometric Transformations. - Alexander Estornell; Leonard Jung; Michael Everett (CoRR, 2025)

Chance-Constrained Convex MPC for Robust Quadruped Locomotion Under Parametric and Additive Uncertainties. - Ananya Trivedi; Sarvesh Prajapati; Mark Zolotas; Michael Everett; Taskin Padir (IEEE Robotics Autom. Lett., 2025)

Real-Time Adaptive Motion Planning via Point Cloud-Guided, Energy-Based Diffusion and Potential Fields. - Wondmgezahu Teshome; Kian Behzad; Octavia I. Camps; Michael Everett; Milad Siami; Mario Sznaier (IEEE Robotics Autom. Lett., 2025)