Nikos Aréchiga

58 papers A* 3A 3B 2C 6Misc 1Journal 28Unranked 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	ConjointNet: Enhancing Conjoint Analysis for Preference Prediction with Representation Learning. CoRR Yanxia Zhang, Francine Chen, Shabnam Hakimi, Totte Harinen, Alex Filipowicz, Yan-Ying Chen, Rumen Iliev, Nikos Aréchiga, Kalani Murakami, Kent Lyons, Charlene C. Wu, Matt Klenk
2024	J	`jnl`	A Safe Preference Learning Approach for Personalization With Applications to Autonomous Vehicles. IEEE Robotics Autom. Lett. Ruya Karagulle, Nikos Aréchiga, Andrew Best, Jonathan A. DeCastro, Necmiye Ozay
2024	J	`jnl`	Bridging Design Gaps: A Parametric Data Completion Approach With Graph Guided Diffusion Models. CoRR Rui Zhou, Chenyang Yuan, Frank Permenter, Yanxia Zhang, Nikos Aréchiga, Matthew Klenk, Faez Ahmed
2024	—	`conf`	Incorporating Logic in Online Preference Learning for Safe Personalization of Autonomous Vehicles. HSCC Ruya Karagulle, Necmiye Ozay, Nikos Aréchiga, Jonathan A. DeCastro, Andrew Best
2024	—	`conf`	Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning. L4DC Mohamad Louai Shehab, Antoine Aspeel, Nikos Aréchiga, Andrew Best, Necmiye Ozay
2024	J	`jnl`	Leveraging Language Models and Bandit Algorithms to Drive Adoption of Battery-Electric Vehicles. CoRR Keiichi Namikoshi, David A. Shamma, Rumen Iliev, Jingchao Fang, Alexandre L. S. Filipowicz, Candice L. Hogan, Charlene C. Wu, Nikos Aréchiga
2024	B	`conf`	On LLM Wizards: Identifying Large Language Models' Behaviors for Wizard of Oz Experiments. IVA Jingchao Fang, Nikos Aréchiga, Keiichi Namikoshi, Nayeli Bravo, Candice Hogan, David A. Shamma
2024	J	`jnl`	On LLM Wizards: Identifying Large Language Models' Behaviors for Wizard of Oz Experiments. CoRR Jingchao Fang, Nikos Aréchiga, Keiichi Namaoshi, Nayeli Bravo, Candice Hogan, David A. Shamma
2024	J	`jnl`	Parametric-ControlNet: Multimodal Control in Foundation Models for Precise Engineering Design Synthesis. CoRR Rui Zhou, Yanxia Zhang, Chenyang Yuan, Frank Permenter, Nikos Aréchiga, Matt Klenk, Faez Ahmed
2024	J	`jnl`	Stylish and Functional: Guided Interpolation Subject to Physical Constraints. CoRR Yan-Ying Chen, Nikos Aréchiga, Chenyang Yuan, Matthew Hong, Matt Klenk, Charlene C. Wu
2024	J	`jnl`	Using LLMs to Model the Beliefs and Preferences of Targeted Populations. CoRR Keiichi Namikoshi, Alex Filipowicz, David A. Shamma, Rumen Iliev, Candice L. Hogan, Nikos Aréchiga
2023	J	`jnl`	A Preference Learning Approach to Develop Safe and Personalizable Autonomous Vehicles. CoRR Ruya Karagulle, Nikos Aréchiga, Andrew Best, Jonathan A. DeCastro, Necmiye Ozay
2023	J	`jnl`	Backpropagation through signal temporal logic specifications: Infusing logical structure into gradient-based methods. Int. J. Robotics Res. Karen Leung, Nikos Aréchiga, Marco Pavone
2023	B	`conf`	Can Behavioral Experts Predict Outcome Heterogeneity? CogSci Rumen Iliev, Alexandre L. S. Filipowicz, Emily Sarah Sumner, Francine Chen, Nikos Aréchiga, Scott A. Carter, Totte Harinen, Kate A. Sieck, Charlene C. Wu
2023	J	`jnl`	Drag-guided diffusion models for vehicle image generation. CoRR Nikos Aréchiga, Frank Permenter, Binyang Song, Chenyang Yuan
2023	—	`conf`	Poster Abstract: Safety Guaranteed Preference Learning Approach for Autonomous Vehicles. HSCC Ruya Karagulle, Nikos Aréchiga, Andrew Best, Jonathan A. DeCastro, Necmiye Ozay
2023	C	`conf`	Robust Testing for Cyber-Physical Systems using Reinforcement Learning. MEMOCODE Xin Qin, Nikos Aréchiga, Jyotirmoy Deshmukh, Andrew Best
2023	J	`jnl`	Surrogate Modeling of Car Drag Coefficient with Depth and Normal Renderings. CoRR Binyang Song, Chenyang Yuan, Frank Permenter, Nikos Aréchiga, Faez Ahmed
2023	—	`conf`	Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledge. CI Anna Kawakami, Luke Guerdan, Yanghuidi Cheng, Kate Glazko, Matthew L. Lee, Scott A. Carter, Nikos Aréchiga, Haiyi Zhu, Kenneth Holstein
2023	J	`jnl`	Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledge. CoRR Anna Kawakami, Luke Guerdan, Yanghuidi Cheng, Matthew L. Lee, Scott A. Carter, Nikos Aréchiga, Kate Glazko, Haiyi Zhu, Kenneth Holstein
2022	—	`conf`	Classification of Driving Behaviors Using STL Formulas: A Comparative Study. FORMATS Ruya Karagulle, Nikos Aréchiga, Jonathan A. DeCastro, Necmiye Ozay
2022	—	`conf`	Finding Label and Model Errors in Perception Data With Learned Observation Assertions. SIGMOD Conference Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter D. Bailis, Matei Zaharia
2022	J	`jnl`	Finding Label and Model Errors in Perception Data With Learned Observation Assertions. CoRR Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter Bailis, Matei Zaharia
2022	—	`conf`	Outlier-robust Inverse Reinforcement Learning and Reward-based Detection of Anomalous Driving Behaviors. ITSC Dan Li, Mohamad Louai Shehab, Zexiang Liu, Nikos Aréchiga, Jonathan A. DeCastro, Necmiye Ozay
2022	A	`conf`	Second-Order Sensitivity Analysis for Bilevel Optimization. AISTATS Robert Dyro, Edward Schmerling, Nikos Aréchiga, Marco Pavone
2022	J	`jnl`	Second-Order Sensitivity Analysis for Bilevel Optimization. CoRR Robert Dyro, Edward Schmerling, Nikos Aréchiga, Marco Pavone
2022	J	`jnl`	Towards a Learner-Centered Explainable AI: Lessons from the learning sciences. CoRR Anna Kawakami, Luke Guerdan, Yang Cheng, Anita Sun, Alison Hu, Kate Glazko, Nikos Aréchiga, Matthew L. Lee, Scott A. Carter, Haiyi Zhu, Kenneth Holstein
2022	J	`jnl`	Understanding and Shifting Preferences for Battery Electric Vehicles. CoRR 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
2021	J	`jnl`	Accelerating Understanding of Scientific Experiments with End to End Symbolic Regression. CoRR Nikos Aréchiga, Francine Chen, Yan-Ying Chen, Yanxia Zhang, Rumen Iliev, Heishiro Toyoda, Kent Lyons
2021	C	`conf`	Back-Propagation Through Signal Temporal Logic Specifications: Infusing Logical Structure into Gradient-Based Methods. WAFR Karen Leung, Nikos Aréchiga, Marco Pavone
2021	J	`jnl`	Certified Control: An Architecture for Verifiable Safety of Autonomous Vehicles. CoRR Daniel Jackson, Valerie Richmond, Mike Wang, Jeff Chow, Uriel Guajardo, Soonho Kong, Sergio Campos, Geoffrey Litt, Nikos Aréchiga
2021	J	`jnl`	Correction to: How to model and prove hybrid systems with KeYmaera: a tutorial on safety. Int. J. Softw. Tools Technol. Transf. Jan-David Quesel, Stefan Mitsch, Sarah M. Loos, Nikos Aréchiga, André Platzer
2021	A*	`conf`	Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization. ICLR Kaidi Cao, Yining Chen, Junwei Lu, Nikos Aréchiga, Adrien Gaidon, Tengyu Ma
2020	J	`jnl`	Back-propagation through Signal Temporal Logic Specifications: Infusing Logical Structure into Gradient-Based Methods. CoRR Karen Leung, Nikos Aréchiga, Marco Pavone
2020	J	`jnl`	Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization. CoRR Kaidi Cao, Yining Chen, Junwei Lu, Nikos Aréchiga, Adrien Gaidon, Tengyu Ma
2020	—	`conf`	Interpretable Policies from Formally-Specified Temporal Properties. ITSC Jonathan A. DeCastro, Karen Leung, Nikos Aréchiga, Marco Pavone
2019	J	`jnl`	Automatic Testing and Falsification with Dynamically Constrained Reinforcement Learning. CoRR Xin Qin, Nikos Aréchiga, Andrew Best, Jyotirmoy V. Deshmukh
2019	C	`conf`	Backpropagation for Parametric STL. IV Karen Leung, Nikos Aréchiga, Marco Pavone
2019	J	`jnl`	Better AI through Logical Scaffolding. CoRR Nikos Aréchiga, Jonathan A. DeCastro, Soonho Kong, Karen Leung
2019	A*	`conf`	Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. NeurIPS Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma
2019	J	`jnl`	Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. CoRR Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma
2019	—	`conf`	Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems. CAV (2) Sicun Gao, James Kapinski, Jyotirmoy V. Deshmukh, Nima Roohi, Armando Solar-Lezama, Nikos Aréchiga, Soonho Kong
2019	C	`conf`	Specifying Safety of Autonomous Vehicles in Signal Temporal Logic. IV Nikos Aréchiga
2017	—	`conf`	Control Parameter Optimization for Autonomous Vehicle Software Using Virtual Prototyping. ISSRE Workshops Siyuan Dai, Joseph Hite, Takato Masuda, Yusuke Kashiba, Nikos Aréchiga, Shinichi Shiraishi, Scott Eisele, Jason Scott, Ted Bapty
2017	—	`conf`	Input Space Partitioning to Enable Massively Parallel Proof. NFM Ashlie B. Hocking, M. Anthony Aiello, John C. Knight, Nikos Aréchiga
2017	A*	`conf`	Learning-Based Abstractions for Nonlinear Constraint Solving. IJCAI Sumanth Dathathri, Nikos Aréchiga, Sicun Gao, Richard M. Murray
2017	—	`conf`	Osiris: A Tool for Abstraction and Verification of Control Software with Lookup Tables. SCAV@CPSWeek Nikos Aréchiga, Sumanth Dathathri, Shashank Vernekar, Nagesh Kathare, Sicun Gao, Shinichi Shiraishi
2016	A	`conf`	Efficient statistical validation of machine learning systems for autonomous driving. ICCAD Weijing Shi, Mohamed Baker Alawieh, Xin Li, Huafeng Yu, Nikos Aréchiga, Nobuyuki Tomatsu
2016	J	`jnl`	How to model and prove hybrid systems with KeYmaera: a tutorial on safety. Int. J. Softw. Tools Technol. Transf. Jan-David Quesel, Stefan Mitsch, Sarah M. Loos, Nikos Aréchiga, André Platzer
2016	—	`conf`	Proving Critical Properties of Simulink Models. HASE Ashlie B. Hocking, M. Anthony Aiello, John C. Knight, Nikos Aréchiga
2015	J	`jnl`	Forward Invariant Cuts to Simplify Proofs of Safety. CoRR Nikos Aréchiga, James Kapinski, Jyotirmoy V. Deshmukh, André Platzer, Bruce H. Krogh
2015	Misc	`conf`	Forward invariant cuts to simplify proofs of safety. EMSOFT Nikos Aréchiga, James Kapinski, Jyotirmoy V. Deshmukh, André Platzer, Bruce H. Krogh
2014	—	`conf`	Numerically-aided Deductive Safety Proof for a Powertrain Control System. NSV Nikos Aréchiga, James Kapinski, Jyotirmoy V. Deshmukh, André Platzer, Bruce H. Krogh
2014	—	`conf`	Simulation-guided lyapunov analysis for hybrid dynamical systems. HSCC James Kapinski, Jyotirmoy V. Deshmukh, Sriram Sankaranarayanan, Nikos Aréchiga
2014	C	`conf`	Using verified control envelopes for safe controller design. ACC Nikos Aréchiga, Bruce H. Krogh
2012	C	`conf`	Using theorem provers to guarantee closed-loop system properties. ACC Nikos Aréchiga, Sarah M. Loos, André Platzer, Bruce H. Krogh
2010	J	`jnl`	Indoor robot gardening: design and implementation. Intell. Serv. Robotics 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
2009	A	`conf`	Building a distributed robot garden. IROS 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