Nikos Aréchiga

According to our database, Nikos Aréchiga authored at least 47 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Safe Preference Learning Approach for Personalization With Applications to Autonomous Vehicles.

Ruya Karagulle, Nikos Aréchiga, Andrew Best, Jonathan A. DeCastro, Necmiye Ozay

IEEE Robotics Autom. Lett., May, 2024

Leveraging Language Models and Bandit Algorithms to Drive Adoption of Battery-Electric Vehicles.

Keiichi Namikoshi, David A. Shamma, Rumen Iliev, Jingchao Fang, Alexandre L. S. Filipowicz, Candice L. Hogan, Charlene C. Wu, Nikos Aréchiga

CoRR, 2024

On LLM Wizards: Identifying Large Language Models' Behaviors for Wizard of Oz Experiments.

Jingchao Fang, Nikos Aréchiga, Keiichi Namaoshi, Nayeli Bravo, Candice Hogan, David A. Shamma

CoRR, 2024

Bridging Design Gaps: A Parametric Data Completion Approach With Graph Guided Diffusion Models.

Rui Zhou, Chenyang Yuan, Frank Permenter, Yanxia Zhang, Nikos Aréchiga, Matt Klenk, Faez Ahmed

CoRR, 2024

Using LLMs to Model the Beliefs and Preferences of Targeted Populations.

Keiichi Namikoshi, Alex Filipowicz, David A. Shamma, Rumen Iliev, Candice L. Hogan, Nikos Aréchiga

CoRR, 2024

Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning.

Mohamad Louai Shehab, Antoine Aspeel, Nikos Aréchiga, Andrew Best, Necmiye Ozay

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Incorporating Logic in Online Preference Learning for Safe Personalization of Autonomous Vehicles.

Ruya Karagulle, Necmiye Ozay, Nikos Aréchiga, Jonathan A. DeCastro, Andrew Best

Proceedings of the 27th ACM International Conference on Hybrid Systems: Computation and Control, 2024

2023

Backpropagation through signal temporal logic specifications: Infusing logical structure into gradient-based methods.

Karen Leung, Nikos Aréchiga, Marco Pavone

Int. J. Robotics Res., May, 2023

A Preference Learning Approach to Develop Safe and Personalizable Autonomous Vehicles.

Ruya Karagulle, Nikos Aréchiga, Andrew Best, Jonathan A. DeCastro, Necmiye Ozay

CoRR, 2023

Drag-guided diffusion models for vehicle image generation.

Nikos Aréchiga, Frank Permenter, Binyang Song, Chenyang Yuan

CoRR, 2023

Surrogate Modeling of Car Drag Coefficient with Depth and Normal Renderings.

Binyang Song, Chenyang Yuan, Frank Permenter, Nikos Aréchiga, Faez Ahmed

CoRR, 2023

Robust Testing for Cyber-Physical Systems using Reinforcement Learning.

Xin Qin, Nikos Aréchiga, Jyotirmoy Deshmukh, Andrew Best

Proceedings of the 21st ACM-IEEE International Symposium on Formal Methods and Models for System Design, 2023

Poster Abstract: Safety Guaranteed Preference Learning Approach for Autonomous Vehicles.

Ruya Karagulle, Nikos Aréchiga, Andrew Best, Jonathan A. DeCastro, Necmiye Ozay

Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control, 2023

Can Behavioral Experts Predict Outcome Heterogeneity?

Rumen Iliev, Alexandre L. S. Filipowicz, Emily Sarah Sumner, Francine Chen, Nikos Aréchiga, Scott A. Carter, Totte Harinen, Kate A. Sieck, Charlene C. Wu

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledge.

Anna Kawakami, Luke Guerdan, Yanghuidi Cheng, Kate Glazko, Matthew L. Lee, Scott A. Carter, Nikos Aréchiga, Haiyi Zhu, Kenneth Holstein

Proceedings of The ACM Collective Intelligence Conference, 2023

2022

Towards a Learner-Centered Explainable AI: Lessons from the learning sciences.

Anna Kawakami, Luke Guerdan, Yang Cheng, Anita Sun, Alison Hu, Kate Glazko, Nikos Aréchiga, Matthew L. Lee, Scott A. Carter, Haiyi Zhu, Kenneth Holstein

CoRR, 2022

Understanding and Shifting Preferences for Battery Electric Vehicles.

Nikos Aréchiga, Francine Chen, Rumen Iliev, Emily Sumner, Scott A. Carter, Alexandre L. S. Filipowicz, Nayeli Suseth Bravo, Monica P. Van, Kate Glazko, Kalani Murakami, Laurent Denoue, Candice Hogan, Katharine Sieck, Charlene C. Wu, Kent Lyons

CoRR, 2022

Finding Label and Model Errors in Perception Data With Learned Observation Assertions.

Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter D. Bailis, Matei Zaharia

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Outlier-robust Inverse Reinforcement Learning and Reward-based Detection of Anomalous Driving Behaviors.

Dan Li, Mohamad Louai Shehab, Zexiang Liu, Nikos Aréchiga, Jonathan A. DeCastro, Necmiye Ozay

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Classification of Driving Behaviors Using STL Formulas: A Comparative Study.

Ruya Karagulle, Nikos Aréchiga, Jonathan A. DeCastro, Necmiye Ozay

Proceedings of the Formal Modeling and Analysis of Timed Systems, 2022

Second-Order Sensitivity Analysis for Bilevel Optimization.

Robert Dyro, Edward Schmerling, Nikos Aréchiga, Marco Pavone

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Correction to: How to model and prove hybrid systems with KeYmaera: a tutorial on safety.

Jan-David Quesel, Stefan Mitsch, Sarah M. Loos, Nikos Aréchiga, André Platzer

Int. J. Softw. Tools Technol. Transf., 2021

Accelerating Understanding of Scientific Experiments with End to End Symbolic Regression.

Nikos Aréchiga, Francine Chen, Yan-Ying Chen, Yanxia Zhang, Rumen Iliev, Heishiro Toyoda, Kent Lyons

CoRR, 2021

Certified Control: An Architecture for Verifiable Safety of Autonomous Vehicles.

Daniel Jackson, Valerie Richmond, Mike Wang, Jeff Chow, Uriel Guajardo, Soonho Kong, Sergio Campos, Geoffrey Litt, Nikos Aréchiga

CoRR, 2021

Back-Propagation Through Signal Temporal Logic Specifications: Infusing Logical Structure into Gradient-Based Methods.

Karen Leung, Nikos Aréchiga, Marco Pavone

Proceedings of the Algorithmic Foundations of Robotics XIV, 2021

Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization.

Kaidi Cao, Yining Chen, Junwei Lu, Nikos Aréchiga, Adrien Gaidon, Tengyu Ma

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Interpretable Policies from Formally-Specified Temporal Properties.

Jonathan A. DeCastro, Karen Leung, Nikos Aréchiga, Marco Pavone

Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

2019

Automatic Testing and Falsification with Dynamically Constrained Reinforcement Learning.

Xin Qin, Nikos Aréchiga, Andrew Best, Jyotirmoy V. Deshmukh

CoRR, 2019

Better AI through Logical Scaffolding.

Nikos Aréchiga, Jonathan A. DeCastro, Soonho Kong, Karen Leung

CoRR, 2019

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss.

Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Backpropagation for Parametric STL.

Karen Leung, Nikos Aréchiga, Marco Pavone

Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019

Specifying Safety of Autonomous Vehicles in Signal Temporal Logic.

Nikos Aréchiga

Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019

Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems.

Sicun Gao, James Kapinski, Jyotirmoy V. Deshmukh, Nima Roohi, Armando Solar-Lezama, Nikos Aréchiga, Soonho Kong

Proceedings of the Computer Aided Verification - 31st International Conference, 2019

2017

Input Space Partitioning to Enable Massively Parallel Proof.

Ashlie B. Hocking, M. Anthony Aiello, John C. Knight, Nikos Aréchiga

Proceedings of the NASA Formal Methods - 9th International Symposium, 2017

Control Parameter Optimization for Autonomous Vehicle Software Using Virtual Prototyping.

Siyuan Dai, Joseph Hite, Takato Masuda, Yusuke Kashiba, Nikos Aréchiga, Shinichi Shiraishi, Scott Eisele, Jason Scott, Ted Bapty

Proceedings of the 2017 IEEE International Symposium on Software Reliability Engineering Workshops, 2017

Learning-Based Abstractions for Nonlinear Constraint Solving.

Sumanth Dathathri, Nikos Aréchiga, Sicun Gao, Richard M. Murray

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Osiris: A Tool for Abstraction and Verification of Control Software with Lookup Tables.

Nikos Aréchiga, Sumanth Dathathri, Shashank Vernekar, Nagesh Kathare, Sicun Gao, Shinichi Shiraishi

Proceedings of the 1st International Workshop on Safe Control of Connected and Autonomous Vehicles, 2017

2016

How to model and prove hybrid systems with KeYmaera: a tutorial on safety.

Jan-David Quesel, Stefan Mitsch, Sarah M. Loos, Nikos Aréchiga, André Platzer

Int. J. Softw. Tools Technol. Transf., 2016

Efficient statistical validation of machine learning systems for autonomous driving.

Weijing Shi, Mohamed Baker Alawieh, Xin Li, Huafeng Yu, Nikos Aréchiga, Nobuyuki Tomatsu

Proceedings of the 35th International Conference on Computer-Aided Design, 2016

Proving Critical Properties of Simulink Models.

Ashlie B. Hocking, M. Anthony Aiello, John C. Knight, Nikos Aréchiga

Proceedings of the 17th IEEE International Symposium on High Assurance Systems Engineering, 2016

2015

Forward invariant cuts to simplify proofs of safety.

Nikos Aréchiga, James Kapinski, Jyotirmoy V. Deshmukh, André Platzer, Bruce H. Krogh

Proceedings of the 2015 International Conference on Embedded Software, 2015

2014

Numerically-aided Deductive Safety Proof for a Powertrain Control System.

Nikos Aréchiga, James Kapinski, Jyotirmoy V. Deshmukh, André Platzer, Bruce H. Krogh

Proceedings of the Seventh and Eighth International Workshops on Numerical Software Verification, 2014

Simulation-guided lyapunov analysis for hybrid dynamical systems.

James Kapinski, Jyotirmoy V. Deshmukh, Sriram Sankaranarayanan, Nikos Aréchiga

Proceedings of the 17th International Conference on Hybrid Systems: Computation and Control (part of CPS Week), 2014

Using verified control envelopes for safe controller design.

Nikos Aréchiga, Bruce H. Krogh

Proceedings of the American Control Conference, 2014

2012

Using theorem provers to guarantee closed-loop system properties.

Nikos Aréchiga, Sarah M. Loos, André Platzer, Bruce H. Krogh

Proceedings of the American Control Conference, 2012

2010

Indoor robot gardening: design and implementation.

Nikolaus Correll, Nikos Aréchiga, Adrienne Bolger, Mario Bollini, Ben Charrow, Adam Clayton, Felipe Dominguez, Kenneth Donahue, Samuel Dyar, Luke Johnson, Huan Liu, Alexander Patrikalakis, Timothy Robertson, Jeremy Smith, Daniel E. Soltero, Melissa Tanner, Lauren White, Daniela Rus

Intell. Serv. Robotics, 2010

2009

Building a distributed robot garden.

Nikolaus Correll, Nikos Aréchiga, Adrienne Bolger, Mario Bollini, Benjamin Charrow, Adam Clayton, Felipe Dominguez, Kenneth Donahue, Samuel Dyar, Luke Johnson, Huan Liu, Alexander Patrikalakis, Timothy Robertson, Jeremy Smith, Daniel E. Soltero, Melissa Tanner, Lauren White, Daniela Rus

Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009