Daniel S. Brown

110 papers A* 22A 4B 2C 1Misc 6Journal 62Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Multi-Layer Sim-to-Real Framework for Gaze-Driven Assistive Neck Exoskeletons. CoRR Colin Rubow, Eric Brewer, Ian Bales, Haohan Zhang, Daniel S. Brown
2026	J	`jnl`	RubRIX: Rubric-Driven Risk Mitigation in Caregiver-AI Interactions. CoRR Drishti Goel, Jeongah Lee, Qiuyue Joy Zhong, Violeta J. Rodriguez, Daniel S. Brown, Ravi Karkar, Dong Whi Yoo, Koustuv Saha
2025	J	`jnl`	Analytical Swarm Chemistry: Characterization and Analysis of Emergent Swarm Behaviors. CoRR Ricardo Vega, Connor Mattson, Kevin Zhu, Daniel S. Brown, Cameron Nowzari
2025	J	`jnl`	Dataset Poisoning Attacks on Behavioral Cloning Policies. CoRR Akansha Kalra, Soumil Datta, Ethan Gilmore, Duc La, Guanhong Tao, Daniel S. Brown
2025	A	`conf`	Discovery and Deployment of Emergent Robot Swarm Behaviors via Representation Learning and Real2Sim2Real Transfer. AAMAS Connor Mattson, Varun Raveendra, Ricardo Vega, Cameron Nowzari, Daniel S. Drew, Daniel S. Brown
2025	J	`jnl`	Discovery and Deployment of Emergent Robot Swarm Behaviors via Representation Learning and Real2Sim2Real Transfer. CoRR Connor Mattson, Varun Raveendra, Ricardo Vega, Cameron Nowzari, Daniel S. Drew, Daniel S. Brown
2025	J	`jnl`	Early Failure Detection in Autonomous Surgical Soft-Tissue Manipulation via Uncertainty Quantification. CoRR Jordan Thompson, Ronald Koe, Anthony Le, Gabriella Goodman, Daniel S. Brown, Alan Kuntz
2025	J	`jnl`	How vulnerable is my policy? Adversarial attacks on modern behavior cloning policies. CoRR Basavasagar Patil, Akansha Kalra, Guanhong Tao, Daniel S. Brown
2025	A*	`conf`	Leveraging Human Input to Enable Robust, Interactive, and Aligned AI Systems. AAAI Daniel S. Brown
2025	J	`jnl`	ProbeMDE: Uncertainty-Guided Active Proprioception for Monocular Depth Estimation in Surgical Robotics. CoRR Britton Jordan, Jordan Thompson, Jesse F. d'Almeida, Hao Li, Nithesh Kumar, Susheela Sharma Stern, Ipek Oguz, Robert J. Webster III, Daniel S. Brown, Alan Kuntz, James M. Ferguson
2025	J	`jnl`	R2BC: Multi-Agent Imitation Learning from Single-Agent Demonstrations. CoRR Connor Mattson, Varun Raveendra, Ellen R. Novoseller, Nicholas R. Waytowich, Vernon J. Lawhern, Daniel S. Brown
2025	A*	`conf`	Toward Zero-Shot User Intent Recognition in Shared Autonomy. HRI Atharv Belsare, Zohre Karimi, Connor Mattson, Daniel S. Brown
2025	J	`jnl`	Toward Zero-Shot User Intent Recognition in Shared Autonomy. CoRR Atharv Belsare, Zohre Karimi, Connor Mattson, Daniel S. Brown
2025	J	`jnl`	Toward robust, interactive, and human-aligned AI systems. AI Mag. Daniel S. Brown
2025	J	`jnl`	Uncertainty Aware Forward and Inverse Kinematics for Tendon-Driven Continuum Robots via Mixture Density Networks. J. Medical Robotics Res. Jordan Thompson, Brian Y. Cho, Daniel S. Brown, Alan Kuntz
2024	J	`jnl`	Agent-Based Emulation for Deploying Robot Swarm Behaviors. CoRR Ricardo Vega, Kevin Zhu, Connor Mattson, Daniel S. Brown, Cameron Nowzari
2024	A*	`conf`	Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning. HRI Tu Trinh, Haoyu Chen, Daniel S. Brown
2024	A*	`conf`	Bayesian Constraint Inference from User Demonstrations Based on Margin-Respecting Preference Models. ICRA Dimitris Papadimitriou, Daniel S. Brown
2024	J	`jnl`	Bayesian Constraint Inference from User Demonstrations Based on Margin-Respecting Preference Models. CoRR Dimitris Papadimitriou, Daniel S. Brown
2024	J	`jnl`	Can Differentiable Decision Trees Enable Interpretable Reward Learning from Human Feedback? RLJ Akansha Kalra, Daniel S. Brown
2024	—	`conf`	Modeling Kinematic Uncertainty of Tendon-Driven Continuum Robots via Mixture Density Networks. ISMR Jordan Thompson, Brian Y. Cho, Daniel S. Brown, Alan Kuntz
2024	J	`jnl`	Modeling Kinematic Uncertainty of Tendon-Driven Continuum Robots via Mixture Density Networks. CoRR Jordan Thompson, Brian Y. Cho, Daniel S. Brown, Alan Kuntz
2024	J	`jnl`	ROIL: Robust Offline Imitation Learning without Trajectories. RLJ Gersi Doko, Guang Yang, Daniel S. Brown, Marek Petrik
2024	J	`jnl`	Representation Alignment from Human Feedback for Cross-Embodiment Reward Learning from Mixed-Quality Demonstrations. RLJ Connor Mattson, Anurag Aribandi, Daniel S. Brown
2024	J	`jnl`	Representation Alignment from Human Feedback for Cross-Embodiment Reward Learning from Mixed-Quality Demonstrations. CoRR Connor Mattson, Anurag Aribandi, Daniel S. Brown
2024	—	`conf`	Reward Learning from Suboptimal Demonstrations with Applications in Surgical Electrocautery. ISMR Zohre Karimi, Shing-Hei Ho, Bao Thach, Alan Kuntz, Daniel S. Brown
2024	J	`jnl`	Reward Learning from Suboptimal Demonstrations with Applications in Surgical Electrocautery. CoRR Zohre Karimi, Shing-Hei Ho, Bao Thach, Alan Kuntz, Daniel S. Brown
2024	—	`conf`	Spiking Neural Networks as a Controller for Emergent Swarm Agents. ICONS Kevin Zhu, Connor Mattson, Shay Snyder, Ricardo Vega, Daniel S. Brown, Maryam Parsa, Cameron Nowzari
2024	J	`jnl`	Spiking Neural Networks as a Controller for Emergent Swarm Agents. CoRR Kevin Zhu, Connor Mattson, Shay Snyder, Ricardo Vega, Daniel S. Brown, Maryam Parsa, Cameron Nowzari
2023	J	`jnl`	Benchmarks and Algorithms for Offline Preference-Based Reward Learning. CoRR Daniel Shin, Anca D. Dragan, Daniel S. Brown
2023	J	`jnl`	Benchmarks and Algorithms for Offline Preference-Based Reward Learning. Trans. Mach. Learn. Res. Daniel Shin, Anca D. Dragan, Daniel S. Brown
2023	J	`jnl`	Can Differentiable Decision Trees Learn Interpretable Reward Functions? CoRR Akansha Kalra, Daniel S. Brown
2023	A*	`conf`	Causal Confusion and Reward Misidentification in Preference-Based Reward Learning. ICLR Jeremy Tien, Jerry Zhi-Yang He, Zackory Erickson, Anca D. Dragan, Daniel S. Brown
2023	A*	`conf`	Contextual Reliability: When Different Features Matter in Different Contexts. ICML Gaurav Rohit Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan, Aditi Raghunathan
2023	J	`jnl`	Contextual Reliability: When Different Features Matter in Different Contexts. CoRR Gaurav R. Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan, Aditi Raghunathan
2023	A*	`conf`	Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models. ICRA Yi Liu, Gaurav Datta, Ellen R. Novoseller, Daniel S. Brown
2023	J	`jnl`	Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models. CoRR Yi Liu, Gaurav Datta, Ellen R. Novoseller, Daniel S. Brown
2023	—	`conf`	Exploring Behavior Discovery Methods for Heterogeneous Swarms of Limited-Capability Robots. MRS Connor Mattson, Jeremy C. Clark, Daniel S. Brown
2023	J	`jnl`	Exploring Behavior Discovery Methods for Heterogeneous Swarms of Limited-Capability Robots. CoRR Connor Mattson, Jeremy C. Clark, Daniel S. Brown
2023	A	`conf`	Leveraging Human Feedback to Evolve and Discover Novel Emergent Behaviors in Robot Swarms. GECCO Connor Mattson, Daniel S. Brown
2023	J	`jnl`	Leveraging Human Feedback to Evolve and Discover Novel Emergent Behaviors in Robot Swarms. CoRR Connor Mattson, Daniel S. Brown
2023	—	`conf`	Player-Centric Procedural Content Generation: Enhancing Runtime Customization by Integrating Real-Time Player Feedback. CHI PLAY (Companion) Nancy N. Blackburn, Michael Gardone, Daniel S. Brown
2023	Misc	`conf`	Quantifying Assistive Robustness Via the Natural-Adversarial Frontier. CoRL Jerry Zhi-Yang He, Daniel S. Brown, Zackory Erickson, Anca D. Dragan
2023	J	`jnl`	Quantifying Assistive Robustness Via the Natural-Adversarial Frontier. CoRR Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown, Anca D. Dragan
2023	A*	`conf`	SIRL: Similarity-based Implicit Representation Learning. HRI Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown, Anca D. Dragan
2023	J	`jnl`	SIRL: Similarity-based Implicit Representation Learning. CoRR Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown, Anca D. Dragan
2023	J	`jnl`	Swarm Mechanics and Swarm Chemistry: A Transdisciplinary Approach for Robot Swarms. CoRR Ricardo Vega, Kevin Zhu, Connor Mattson, Daniel S. Brown, Cameron Nowzari
2023	A*	`conf`	The Effect of Modeling Human Rationality Level on Learning Rewards from Multiple Feedback Types. AAAI Gaurav R. Ghosal, Matthew Zurek, Daniel S. Brown, Anca D. Dragan
2022	J	`jnl`	A Study of Causal Confusion in Preference-Based Reward Learning. CoRR Jeremy Tien, Jerry Zhi-Yang He, Zackory Erickson, Anca D. Dragan, Daniel S. Brown
2022	J	`jnl`	Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning. CoRR Tu Trinh, Daniel S. Brown
2022	J	`jnl`	Bayesian Methods for Constraint Inference in Reinforcement Learning. Trans. Mach. Learn. Res. Dimitris Papadimitriou, Usman Anwar, Daniel S. Brown
2022	A*	`conf`	LEGS: Learning Efficient Grasp Sets for Exploratory Grasping. ICRA Letian Fu, Michael Danielczuk, Ashwin Balakrishna, Daniel S. Brown, Jeffrey Ichnowski, Eugen Solowjow, Ken Goldberg
2022	Misc	`conf`	Learning Representations that Enable Generalization in Assistive Tasks. CoRL Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown, Aditi Raghunathan, Anca D. Dragan
2022	J	`jnl`	Learning Representations that Enable Generalization in Assistive Tasks. CoRR Jerry Zhi-Yang He, Aditi Raghunathan, Daniel S. Brown, Zackory Erickson, Anca D. Dragan
2022	—	`conf`	Learning Switching Criteria for Sim2Real Transfer of Robotic Fabric Manipulation Policies. CASE Satvik Sharma, Ellen R. Novoseller, Vainavi Viswanath, Zaynah Javed, Rishi Parikh, Ryan Hoque, Ashwin Balakrishna, Daniel S. Brown, Ken Goldberg
2022	J	`jnl`	Learning Switching Criteria for Sim2Real Transfer of Robotic Fabric Manipulation Policies. CoRR Satvik Sharma, Ellen R. Novoseller, Vainavi Viswanath, Zaynah Javed, Rishi Parikh, Ryan Hoque, Ashwin Balakrishna, Daniel S. Brown, Ken Goldberg
2022	A*	`conf`	Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations. NeurIPS Albert Wilcox, Ashwin Balakrishna, Jules Dedieu, Wyame Benslimane, Daniel S. Brown, Ken Goldberg
2022	J	`jnl`	Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations. CoRR Albert Wilcox, Ashwin Balakrishna, Jules Dedieu, Wyame Benslimane, Daniel S. Brown, Ken Goldberg
2022	A	`conf`	Teaching Robots to Span the Space of Functional Expressive Motion. IROS Arjun Sripathy, Andreea Bobu, Zhongyu Li, Koushil Sreenath, Daniel S. Brown, Anca D. Dragan
2022	J	`jnl`	Teaching Robots to Span the Space of Functional Expressive Motion. CoRR Arjun Sripathy, Andreea Bobu, Zhongyu Li, Koushil Sreenath, Daniel S. Brown, Anca D. Dragan
2022	J	`jnl`	The Effect of Modeling Human Rationality Level on Learning Rewards from Multiple Feedback Types. CoRR Gaurav R. Ghosal, Matthew Zurek, Daniel S. Brown, Anca D. Dragan
2021	A*	`conf`	Dynamically Switching Human Prediction Models for Efficient Planning. ICRA Arjun Sripathy, Andreea Bobu, Daniel S. Brown, Anca D. Dragan
2021	J	`jnl`	Dynamically Switching Human Prediction Models for Efficient Planning. CoRR Arjun Sripathy, Andreea Bobu, Daniel S. Brown, Anca D. Dragan
2021	—	`conf`	Kit-Net: Self-Supervised Learning to Kit Novel 3D Objects into Novel 3D Cavities. CASE Shivin Devgon, Jeffrey Ichnowski, Michael Danielczuk, Daniel S. Brown, Ashwin Balakrishna, Shirin Joshi, Eduardo M. C. Rocha, Eugen Solowjow, Ken Goldberg
2021	J	`jnl`	Kit-Net: Self-Supervised Learning to Kit Novel 3D Objects into Novel 3D Cavities. CoRR Shivin Devgon, Jeffrey Ichnowski, Michael Danielczuk, Daniel S. Brown, Ashwin Balakrishna, Shirin Joshi, Eduardo M. C. Rocha, Eugen Solowjow, Ken Goldberg
2021	J	`jnl`	LEGS: Learning Efficient Grasp Sets for Exploratory Grasping. CoRR Letian Fu, Michael Danielczuk, Ashwin Balakrishna, Daniel S. Brown, Jeffrey Ichnowski, Eugen Solowjow, Ken Goldberg
2021	—	`conf`	LazyDAgger: Reducing Context Switching in Interactive Imitation Learning. CASE Ryan Hoque, Ashwin Balakrishna, Carl Putterman, Michael Luo, Daniel S. Brown, Daniel Seita, Brijen Thananjeyan, Ellen R. Novoseller, Ken Goldberg
2021	J	`jnl`	LazyDAgger: Reducing Context Switching in Interactive Imitation Learning. CoRR Ryan Hoque, Ashwin Balakrishna, Carl Putterman, Michael Luo, Daniel S. Brown, Daniel Seita, Brijen Thananjeyan, Ellen R. Novoseller, Ken Goldberg
2021	J	`jnl`	Offline Preference-Based Apprenticeship Learning. CoRR Daniel Shin, Daniel S. Brown
2021	—	`conf`	Optimal Cost Design for Model Predictive Control. L4DC Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan
2021	J	`jnl`	Optimal Cost Design for Model Predictive Control. CoRR Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan
2021	A*	`conf`	Policy Gradient Bayesian Robust Optimization for Imitation Learning. ICML Zaynah Javed, Daniel S. Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca D. Dragan, Ken Goldberg
2021	J	`jnl`	Policy Gradient Bayesian Robust Optimization for Imitation Learning. CoRR Zaynah Javed, Daniel S. Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca D. Dragan, Ken Goldberg
2021	A*	`conf`	Situational Confidence Assistance for Lifelong Shared Autonomy. ICRA Matthew Zurek, Andreea Bobu, Daniel S. Brown, Anca D. Dragan
2021	J	`jnl`	Situational Confidence Assistance for Lifelong Shared Autonomy. CoRR Matthew Zurek, Andreea Bobu, Daniel S. Brown, Anca D. Dragan
2021	Misc	`conf`	ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning. CoRL Ryan Hoque, Ashwin Balakrishna, Ellen R. Novoseller, Albert Wilcox, Daniel S. Brown, Ken Goldberg
2021	J	`jnl`	ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning. CoRR Ryan Hoque, Ashwin Balakrishna, Ellen R. Novoseller, Albert Wilcox, Daniel S. Brown, Ken Goldberg
2021	A*	`conf`	Value Alignment Verification. ICML Daniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum
2020	A*	`conf`	Bayesian Robust Optimization for Imitation Learning. NeurIPS Daniel S. Brown, Scott Niekum, Marek Petrik
2020	J	`jnl`	Bayesian Robust Optimization for Imitation Learning. CoRR Daniel S. Brown, Scott Niekum, Marek Petrik
2020	Misc	`conf`	Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects. CoRL Michael Danielczuk, Ashwin Balakrishna, Daniel S. Brown, Ken Goldberg
2020	J	`jnl`	Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects. CoRR Michael Danielczuk, Ashwin Balakrishna, Daniel S. Brown, Shivin Devgon, Ken Goldberg
2020	A*	`conf`	Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences. ICML Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
2020	J	`jnl`	Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences. CoRR Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
2020	J	`jnl`	Value Alignment Verification. CoRR Daniel S. Brown, Jordan Schneider, Scott Niekum
2019	Misc	`conf`	Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations. CoRL Daniel S. Brown, Wonjoon Goo, Scott Niekum
2019	J	`jnl`	Deep Bayesian Reward Learning from Preferences. CoRR Daniel S. Brown, Scott Niekum
2019	A*	`conf`	Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. ICML Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum
2019	J	`jnl`	Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. CoRR Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum
2019	A*	`conf`	Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications. AAAI Daniel S. Brown, Scott Niekum
2019	J	`jnl`	Ranking-Based Reward Extrapolation without Rankings. CoRR Daniel S. Brown, Wonjoon Goo, Scott Niekum
2019	J	`jnl`	Risk-Aware Active Inverse Reinforcement Learning. CoRR Daniel S. Brown, Yuchen Cui, Scott Niekum
2018	A*	`conf`	Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning. AAAI Daniel S. Brown, Scott Niekum
2018	J	`jnl`	LAAIR: A Layered Architecture for Autonomous Interactive Robots. CoRR Yuqian Jiang, Nick Walker, Minkyu Kim, Nicolas Brissonneau, Daniel S. Brown, Justin W. Hart, Scott Niekum, Luis Sentis, Peter Stone
2018	J	`jnl`	Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications. CoRR Daniel S. Brown, Scott Niekum
2018	Misc	`conf`	Risk-Aware Active Inverse Reinforcement Learning. CoRL Daniel S. Brown, Yuchen Cui, Scott Niekum
2017	J	`jnl`	Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning. CoRR Daniel S. Brown, Scott Niekum
2017	J	`jnl`	Exact and Heuristic Algorithms for Risk-Aware Stochastic Physical Search. Comput. Intell. Daniel S. Brown, Jeffrey Hudack, Nathaniel Gemelli, Bikramjit Banerjee
2017	—	`conf`	Toward Probabilistic Safety Bounds for Robot Learning from Demonstration. AAAI Fall Symposia Daniel S. Brown, Scott Niekum
2016	A*	`conf`	Classifying swarm behavior via compressive subspace learning. ICRA Matthew Berger, Lee M. Seversky, Daniel S. Brown
2016	—	`conf`	Discovery and Exploration of Novel Swarm Behaviors Given Limited Robot Capabilities. DARS Daniel S. Brown, Ryan Turner, Oliver Hennigh, Steven Loscalzo
2016	J	`jnl`	Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm. EAI Endorsed Trans. Collab. Comput. Matthew Johnson, Daniel S. Brown
2016	J	`jnl`	Two invariants of human-swarm interaction. J. Hum. Robot Interact. Daniel S. Brown, Michael A. Goodrich, Shin-Young Jung, Sean Kerman
2015	—	`conf`	Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm. BICT Matthew Johnson, Daniel S. Brown
2015	C	`conf`	Multiobjective Optimization for the Stochastic Physical Search Problem. IEA/AIE Jeffrey Hudack, Nathaniel Gemelli, Daniel S. Brown, Steven Loscalzo, Jae C. Oh
2015	—	`conf`	k-Agent Sufficiency for Multiagent Stochastic Physical Search Problems. ADT Daniel S. Brown, Steven Loscalzo, Nathaniel Gemelli
2014	B	`conf`	Balancing human and inter-agent influences for shared control of bio-inspired collectives. SMC Daniel S. Brown, Shin-Young Jun, Michael A. Goodrich
2014	A*	`conf`	Human-swarm interactions based on managing attractors. HRI Daniel S. Brown, Sean C. Kerman, Michael A. Goodrich
2014	A	`conf`	Limited bandwidth recognition of collective behaviors in bio-inspired swarms. AAMAS Daniel S. Brown, Michael A. Goodrich
2013	B	`conf`	Shaping Couzin-Like Torus Swarms through Coordinated Mediation. SMC Shin-Young Jun, Daniel S. Brown, Michael A. Goodrich