Kochenderfer, Mykel J.

49 publications

JAIR 2026 Backward Monte Carlo Tree Search: Charting Unsafe Regions in the Belief-Space Anil Yildiz, Esen Yel, Marcell Vazquez-Chanlatte, Kyle Hollins Wray, Mykel J. Kochenderfer, Stefan J. Witwicki

AAAI 2025 Enhanced Importance Sampling Through Latent Space Exploration in Normalizing Flows Liam Anthony Kruse, Alexandros E. Tzikas, Harrison Delecki, Mansur M. Arief, Mykel J. Kochenderfer

AAAI 2025 Semi-Markovian Planning to Coordinate Aerial and Maritime Medical Evacuation Platforms Mahdi Al-Husseini, Kyle Hollins Wray, Mykel J. Kochenderfer

NeurIPS 2024 BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices Anka Reuel, Amelia Hardy, Chandler Smith, Max Lamparth, Malcolm Hardy, Mykel J. Kochenderfer

IJCAI 2024 ConstrainedZero: Chance-Constrained POMDP Planning Using Learned Probabilistic Failure Surrogates and Adaptive Safety Constraints Robert J. Moss, Arec L. Jamgochian, Johannes Fischer, Anthony Corso, Mykel J. Kochenderfer

IJCAI 2024 Optimality Guarantees for Particle Belief Approximation of POMDPs (Abstract Reprint) Michael H. Lim, Tyler J. Becker, Mykel J. Kochenderfer, Claire J. Tomlin, Zachary Sunberg

NeurIPS 2023 AVOIDDS: Aircraft Vision-Based Intruder Detection Dataset and Simulator Elysia Smyers, Sydney Katz, Anthony Corso, Mykel J Kochenderfer

NeurIPS 2023 Conformal Prediction for Uncertainty-Aware Planning with Diffusion Dynamics Model Jiankai Sun, Yiqi Jiang, Jianing Qiu, Parth Nobel, Mykel J Kochenderfer, Mac Schwager

MLJ 2023 Generating Probabilistic Safety Guarantees for Neural Network Controllers Sydney M. Katz, Kyle D. Julian, Christopher A. Strong, Mykel J. Kochenderfer

MLJ 2023 Global Optimization of Objective Functions Represented by ReLU Networks Christopher A. Strong, Haoze Wu, Aleksandar Zeljic, Kyle D. Julian, Guy Katz, Clark W. Barrett, Mykel J. Kochenderfer

MLJ 2023 Guest Editorial: Special Issue on Robust Machine Learning Ransalu Senanayake, Daniel J. Fremont, Mykel J. Kochenderfer, Alessio R. Lomuscio, Dragos D. Margineantu, Cheng Soon Ong

JAIR 2023 Optimality Guarantees for Particle Belief Approximation of POMDPs Michael H. Lim, Tyler J. Becker, Mykel J. Kochenderfer, Claire J. Tomlin, Zachary N. Sunberg

AAAI 2022 A Gray Box Model for Characterizing Driver Behavior Soyeon Jung, Ransalu Senanayake, Mykel J. Kochenderfer

NeurIPS 2022 Collaborative Decision Making Using Action Suggestions Dylan Asmar, Mykel J Kochenderfer

NeurIPS 2022 Interaction Modeling with Multiplex Attention Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang, Jiachen Li, Mykel J Kochenderfer, Jiajun Wu, Nick Haber

AAAI 2022 Interpretable Local Tree Surrogate Policies John Mern, Sidhart Krishnan, Anil Yildiz, Kyle Hatch, Mykel J. Kochenderfer

JMLR 2022 OVERT: An Algorithm for Safety Verification of Neural Network Control Policies for Nonlinear Systems Chelsea Sidrane, Amir Maleki, Ahmed Irfan, Mykel J. Kochenderfer

AAAI 2022 Recursive Reasoning Graph for Multi-Agent Reinforcement Learning Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer

NeurIPS 2022 Risk-Driven Design of Perception Systems Anthony Corso, Sydney Katz, Craig Innes, Xin Du, Subramanian Ramamoorthy, Mykel J Kochenderfer

IJCAI 2022 Scalable Anytime Planning for Multi-Agent MDPs (Extended Abstract) Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer

JAIR 2022 Scalable Online Planning for Multi-Agent MDPs Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer

AAAI 2022 Using Adaptive Stress Testing to Identify Paths to Ethical Dilemmas in Autonomous Systems Ann-Katrin Reuel, Mark Koren, Anthony Corso, Mykel J. Kochenderfer

JAIR 2021 A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems Anthony Corso, Robert J. Moss, Mark Koren, Ritchie Lee, Mykel J. Kochenderfer

AAAI 2021 Bayesian Optimized Monte Carlo Planning John Mern, Anil Yildiz, Zachary Sunberg, Tapan Mukerji, Mykel J. Kochenderfer

JAIR 2021 Efficient Large-Scale Multi-Drone Delivery Using Transit Networks Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone

NeurIPS 2021 Evidential SoftMax for Sparse Multimodal Distributions in Deep Generative Models Phil Chen, Mikhal Itkina, Ransalu Senanayake, Mykel J Kochenderfer

AAAI 2021 Improved POMDP Tree Search Planning with Prioritized Action Branching John Mern, Anil Yildiz, Lawrence Bush, Tapan Mukerji, Mykel J. Kochenderfer

AAAI 2021 Transfer Learning for Efficient Iterative Safety Validation Anthony Corso, Mykel J. Kochenderfer

JAIR 2020 Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer

NeurIPS 2020 Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders Masha Itkina, Boris Ivanovic, Ransalu Senanayake, Mykel J Kochenderfer, Marco Pavone

NeurIPS 2020 Handling Missing Data with Graph Representation Learning Jiaxuan You, Xiaobai Ma, Yi Ding, Mykel J Kochenderfer, Jure Leskovec

AAAI 2020 Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer

NeurIPS 2020 Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette, Alessandro Lazaric, Mykel J Kochenderfer, Emma Brunskill

NeurIPS 2019 Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model Andrea Zanette, Mykel J Kochenderfer, Emma Brunskill

IJCAI 2019 Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control Jeremy Morton, Freddie D. Witherden, Mykel J. Kochenderfer

NeurIPS 2019 Limiting Extrapolation in Linear Approximate Value Iteration Andrea Zanette, Alessandro Lazaric, Mykel J Kochenderfer, Emma Brunskill

IJCAI 2019 Monte Carlo Tree Search for Policy Optimization Xiaobai Ma, Katherine Rose Driggs-Campbell, Zongzhang Zhang, Mykel J. Kochenderfer

JAIR 2019 Unifying System Health Management and Automated Decision Making Edward Balaban, Stephen B. Johnson, Mykel J. Kochenderfer

NeurIPS 2018 Amortized Inference Regularization Rui Shu, Hung H Bui, Shengjia Zhao, Mykel J Kochenderfer, Stefano Ermon

NeurIPS 2018 Deep Dynamical Modeling and Control of Unsteady Fluid Flows Jeremy Morton, Antony Jameson, Mykel J Kochenderfer, Freddie Witherden

ECML-PKDD 2018 Robust Super-Level Set Estimation Using Gaussian Processes Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer

JAIR 2017 Learning Discrete Bayesian Networks from Continuous Data Yi-Chun Chen, Tim Allan Wheeler, Mykel J. Kochenderfer

MLOSS 2017 POMDPs.jl: A Framework for Sequential Decision Making Under Uncertainty Maxim Egorov, Zachary N. Sunberg, Edward Balaban, Tim A. Wheeler, Jayesh K. Gupta, Mykel J. Kochenderfer

IJCAI 2017 Weighted Double Q-Learning Zongzhang Zhang, Zhiyuan Pan, Mykel J. Kochenderfer

AAAI 2016 Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs Philipp Robbel, Frans A. Oliehoek, Mykel J. Kochenderfer

AAAI 2016 Target Surveillance in Adversarial Environments Using POMDPs Maxim Egorov, Mykel J. Kochenderfer, Jaak J. Uudmae

UAI 2012 Predicting the Behavior of Interacting Humans by Fusing Data from Multiple Sources Erik J. Schlicht, Ritchie Lee, David H. Wolpert, Mykel J. Kochenderfer, Brendan D. Tracey

AAAI 2005 Adaptive Modeling and Planning for Reactive Agents Mykel J. Kochenderfer

AAAI 2004 Common Sense Data Acquisition for Indoor Mobile Robots Rakesh Gupta, Mykel J. Kochenderfer