Analysis of Nonlinear Input Impedance Matching in Active Frequency Multipliers. - Jessi E. Johnson; Andrew Silva; George R. Branner (IEICE Trans. Inf. Syst., 2005)

Effects of Interruptibility-Aware Robot Behavior. - Siddhartha Banerjee; Andrew Silva; Karen M. Feigh; Sonia Chernova (CoRR, 2018)

Robot Classification of Human Interruptibility and a Study of Its Effects. - Siddhartha Banerjee; Andrew Silva; Sonia Chernova (ACM Trans. Hum. Robot Interact., 2018)

Unsupervised Role Discovery Using Temporal Observations of Agents. - Andrew Silva; Sonia Chernova (AAMAS, 2019)

Action2Vec: A Crossmodal Embedding Approach to Action Learning. - Meera Hahn; Andrew Silva; James M. Rehg (CoRR, 2019)

ProLoNets: Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning. - Andrew Silva; Matthew C. Gombolay (CoRR, 2019)

Safe Coordination of Human-Robot Firefighting Teams. - Esmaeil Seraj; Andrew Silva; Matthew C. Gombolay (CoRR, 2019)

Personalized Apprenticeship Learning from Heterogeneous Decision-Makers. - Rohan R. Paleja; Andrew Silva; Matthew C. Gombolay (CoRR, 2019)

Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning. - Andrew Silva; Matthew C. Gombolay; Taylor W. Killian; Ivan Dario Jimenez Jimenez; Sung-Hyun Son (AISTATS, 2020)

Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User Demonstrations. - Rohan R. Paleja; Andrew Silva; Letian Chen; Matthew C. Gombolay (NeurIPS, 2020)

Using Cross-Loss Influence Functions to Explain Deep Network Representations. - Andrew Silva; Rohit Chopra; Matthew C. Gombolay (CoRR, 2020)

Encoding Human Domain Knowledge to Warm Start Reinforcement Learning. - Andrew Silva; Matthew C. Gombolay (AAAI, 2021)

Multimodal Punctuation Prediction with Contextual Dropout. - Andrew Silva; Barry-John Theobald; Nicholas Apostoloff (ICASSP, 2021)

Towards a Comprehensive Understanding and Accurate Evaluation of Societal Biases in Pre-Trained Transformers. - Andrew Silva; Pradyumna Tambwekar; Matthew C. Gombolay (NAACL-HLT, 2021)

Interpretable Policy Specification and Synthesis through Natural Language and RL. - Pradyumna Tambwekar; Andrew Silva; Nakul Gopalan; Matthew C. Gombolay (CoRR, 2021)

Cross-Loss Influence Functions to Explain Deep Network Representations. - Andrew Silva; Rohit Chopra; Matthew C. Gombolay (AISTATS, 2022)

Learning Interpretable, High-Performing Policies for Autonomous Driving. - Rohan R. Paleja; Yaru Niu; Andrew Silva; Chace Ritchie; Sugju Choi; Matthew C. Gombolay (Robotics: Science and Systems, 2022)

Multi-UAV planning for cooperative wildfire coverage and tracking with quality-of-service guarantees. - Esmaeil Seraj; Andrew Silva; Matthew C. Gombolay (Auton. Agents Multi Agent Syst., 2022)

Learning Interpretable, High-Performing Policies for Continuous Control Problems. - Rohan R. Paleja; Yaru Niu; Andrew Silva; Chace Ritchie; Sugju Choi; Matthew C. Gombolay (CoRR, 2022)

FedEmbed: Personalized Private Federated Learning. - Andrew Silva; Katherine Metcalf; Nicholas Apostoloff; Barry-John Theobald (CoRR, 2022)

FedPC: Federated Learning for Language Generation with Personal and Context Preference Embeddings. - Andrew Silva; Pradyumna Tambwekar; Matthew C. Gombolay (CoRR, 2022)

LanCon-Learn: Learning With Language to Enable Generalization in Multi-Task Manipulation. - Andrew Silva; Nina Moorman; William Silva; Zulfiqar Zaidi; Nakul Gopalan; Matthew C. Gombolay (IEEE Robotics Autom. Lett., 2022)

FedPerC: Federated Learning for Language Generation with Personal and Context Preference Embeddings. - Andrew Silva; Pradyumna Tambwekar; Matthew C. Gombolay (EACL (Findings), 2023)

Interpretable Reinforcement Learning for Robotics and Continuous Control. - Rohan R. Paleja; Letian Chen; Yaru Niu; Andrew Silva; Zhaoxin Li; Songan Zhang; Chace Ritchie; Sugju Choi; Kimberlee Chestnut Chang; Hongtei Eric Tseng; Yan Wang 075; Subramanya Nageshrao; et al. (CoRR, 2023)

Interactive and Explainable Methods in Machine Learning with Humans. - Andrew Silva (2023)

Explainable Artificial Intelligence: Evaluating the Objective and Subjective Impacts of xAI on Human-Agent Interaction. - Andrew Silva; Mariah Schrum; Erin Hedlund-Botti; Nakul Gopalan; Matthew C. Gombolay (Int. J. Hum. Comput. Interact., 2023)

Natural Language Specification of Reinforcement Learning Policies Through Differentiable Decision Trees. - Pradyumna Tambwekar; Andrew Silva; Nakul Gopalan; Matthew C. Gombolay (IEEE Robotics Autom. Lett., 2023)

Dreaming to Assist: Learning to Align with Human Objectives for Shared Control in High-Speed Racing. - Jonathan A. DeCastro; Andrew Silva; Deepak E. Gopinath; Emily Sumner; Thomas Matrai Balch; Laporsha Dees; Guy Rosman (CoRL, 2024)

Towards Balancing Preference and Performance through Adaptive Personalized Explainability. - Andrew Silva; Pradyumna Tambwekar; Mariah Schrum; Matthew C. Gombolay (HRI, 2024)

Shared Autonomy for Proximal Teaching. - Megha Srivastava; Reihaneh Iranmanesh; Yuchen Cui; Deepak Edakkattil Gopinath; Emily Sarah Sumner; Andrew Silva; Laporsha Dees; Guy Rosman; Dorsa Sadigh (HRI, 2025)

ReGen: Generative Robot Simulation via Inverse Design. - Phat Tan Nguyen; Tsun-Hsuan Wang; Zhang-Wei Hong; Erfan Aasi; Andrew Silva; Guy Rosman; Sertac Karaman; Daniela Rus (ICLR, 2025)