Setting That Mouse for Tracking Tasks. - Ransalu Senanayake; Ravindra S. Goonetilleke (HCI (23), 2013)

Moment invariant features for automatic identification of critical malaria parasites. - Ahalya Ravendran; K. W. T. Roshali T. de Silva; Ransalu Senanayake (ICIIS, 2015)

Targeted-Tracking With Pointing Devices. - Ransalu Senanayake; Ravindra S. Goonetilleke; Errol R. Hoffmann (IEEE Trans. Hum. Mach. Syst., 2015)

Predicting Spatio-Temporal Propagation of Seasonal Influenza Using Variational Gaussian Process Regression. - Ransalu Senanayake; Simon Timothy O'Callaghan; Fabio Ramos 001 (AAAI, 2016)

Spatio-Temporal Hilbert Maps for Continuous Occupancy Representation in Dynamic Environments. - Ransalu Senanayake; Lionel Ott; Simon Timothy O'Callaghan; Fabio Tozeto Ramos (NIPS, 2016)

Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping. - Ransalu Senanayake; Fabio Ramos 001 (CoRL, 2017)

Learning highly dynamic environments with stochastic variational inference. - Ransalu Senanayake; Simon Timothy O'Callaghan; Fabio Tozeto Ramos (ICRA, 2017)

Building Continuous Occupancy Maps With Moving Robots. - Ransalu Senanayake; Fabio Ramos 001 (AAAI, 2018)

Automorphing Kernels for Nonstationarity in Mapping Unstructured Environments. - Ransalu Senanayake; Anthony Tompkins; Fabio Ramos 001 (CoRL, 2018)

Directional Grid Maps: Modeling Multimodal Angular Uncertainty in Dynamic Environments. - Ransalu Senanayake; Fabio Ramos 001 (IROS, 2018)

Black Box Quantiles for Kernel Learning. - Anthony Tompkins; Ransalu Senanayake; Philippe Morere; Fabio Ramos 001 (AISTATS, 2019)

Time-varying Pedestrian Flow Models for Service Robots. - Tomás Vintr; Sergi Molina Mellado; Ransalu Senanayake; George Broughton; Zhi Yan 001; Jirí Ulrich; Tomasz Piotr Kucner; Chittaranjan Srinivas Swaminathan; Filip Majer; Mária Stachová; Achim J. Lilienthal; Tomás Krajník (ECMR, 2019)

Dynamic Hilbert Maps: Real-Time Occupancy Predictions in Changing Environments. - Vitor Guizilini; Ransalu Senanayake; Fabio Ramos 001 (ICRA, 2019)

Continuous Occupancy Map Fusion with Fast Bayesian Hilbert Maps. - Weiming Zhi; Lionel Ott; Ransalu Senanayake; Fabio Ramos 001 (ICRA, 2019)

Dynamic Hilbert Maps: Real-Time Occupancy Predictions in Changing Environment. - Vitor Guizilini; Ransalu Senanayake; Fabio Ramos 001 (CoRR, 2019)

Spatiotemporal Learning of Directional Uncertainty in Urban Environments With Kernel Recurrent Mixture Density Networks. - Weiming Zhi; Ransalu Senanayake; Lionel Ott; Fabio Ramos 001 (IEEE Robotics Autom. Lett., 2019)

Online Parameter Estimation for Human Driver Behavior Prediction. - Raunak P. Bhattacharyya; Ransalu Senanayake; Kyle Brown; Mykel J. Kochenderfer (ACC, 2020)

Directional Primitives for Uncertainty-Aware Motion Estimation in Urban Environments. - Ransalu Senanayake; Maneekwan Toyungyernsub; Mingyu Wang 002; Mykel J. Kochenderfer; Mac Schwager (ITSC, 2020)

Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders. - Masha Itkina; Boris Ivanovic; Ransalu Senanayake; Mykel J. Kochenderfer; Marco Pavone 001 (NeurIPS, 2020)

Online Domain Adaptation for Occupancy Mapping. - Anthony Tompkins; Ransalu Senanayake; Fabio Ramos 001 (Robotics: Science and Systems, 2020)

Double-Prong ConvLSTM for Spatiotemporal Occupancy Prediction in Dynamic Environments. - Maneekwan Toyungyernsub; Masha Itkina; Ransalu Senanayake; Mykel J. Kochenderfer (ICRA, 2021)

3D Radar Velocity Maps for Uncertain Dynamic Environments. - Ransalu Senanayake; Kyle Beltran Hatch; Jason Zheng; Mykel J. Kochenderfer (IROS, 2021)

Out-of-Distribution Detection for Automotive Perception. - Julia Nitsch; Masha Itkina; Ransalu Senanayake; Juan I. Nieto 001; Max Schmidt; Roland Siegwart; Mykel J. Kochenderfer; Cesar Cadena 001 (ITSC, 2021)

Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models. - Phil Chen; Masha Itkina; Ransalu Senanayake; Mykel J. Kochenderfer (NeurIPS, 2021)

Out of Distribution Detection and Adversarial Attacks on Deep Neural Networks for Robust Medical Image Analysis. - Anisie Uwimana; Ransalu Senanayake (CoRR, 2021)

A Gray Box Model for Characterizing Driver Behavior. - Soyeon Jung; Ransalu Senanayake; Mykel J. Kochenderfer (SafeAI@AAAI, 2022)

Infrastructure-Enabled Autonomy: An Attention Mechanism for Occlusion Handling. - Victoria Magdalena Dax; Mykel J. Kochenderfer; Ransalu Senanayake; Umair Ibrahim (ICRA, 2022)

How Do We Fail? Stress Testing Perception in Autonomous Vehicles. - Harrison Delecki; Masha Itkina; Bernard Lange; Ransalu Senanayake; Mykel J. Kochenderfer (IROS, 2022)

FIG-OP: Exploring Large-Scale Unknown Environments on a Fixed Time Budget. - Oriana Peltzer; Amanda Bouman; Sung-Kyun Kim; Ransalu Senanayake; Joshua Ott; Harrison Delecki; Mamoru Sobue; Mykel J. Kochenderfer; Mac Schwager; Joel Burdick; Ali-akbar Agha-mohammadi (IROS, 2022)

Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills. - Julia Tan; Ransalu Senanayake; Fabio Ramos 001 (IROS, 2022)

Uncertainty-Aware Online Merge Planning with Learned Driver Behavior. - Liam A. Kruse; Esen Yel; Ransalu Senanayake; Mykel J. Kochenderfer (ITSC, 2022)

Graphical Games for UAV Swarm Control Under Time-Varying Communication Networks. - Malintha Fernando; Ransalu Senanayake; Ariful Azad; Martin Swany (CoRR, 2022)

Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning. - Bertrand Charpentier; Ransalu Senanayake; Mykel J. Kochenderfer; Stephan Günnemann (CoRR, 2022)

CoCo Games: Graphical Game-Theoretic Swarm Control for Communication-Aware Coverage. - Malintha Fernando; Ransalu Senanayake; Martin Swany (IEEE Robotics Autom. Lett., 2022)

A Hybrid Rule-Based and Data-Driven Approach to Driver Modeling Through Particle Filtering. - Raunak P. Bhattacharyya; Soyeon Jung; Liam A. Kruse; Ransalu Senanayake; Mykel J. Kochenderfer (IEEE Trans. Intell. Transp. Syst., 2022)

Model Predictive Optimized Path Integral Strategies. - Dylan M. Asmar; Ransalu Senanayake; Shawn Manuel; Mykel J. Kochenderfer (ICRA, 2023)

Graph Attention Multi-Agent Fleet Autonomy for Advanced Air Mobility. - Malintha Fernando; Ransalu Senanayake; Heeyoul Choi; Martin Swany (Robotics: Science and Systems, 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 (Mach. Learn., 2023)

Modeling Human Driving Behavior Through Generative Adversarial Imitation Learning. - Raunak P. Bhattacharyya; Blake Wulfe; Derek J. Phillips; Alex Kuefler; Jeremy Morton; Ransalu Senanayake; Mykel J. Kochenderfer (IEEE Trans. Intell. Transp. Syst., 2023)

Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models. - Som Sagar; Aditya Taparia; Ransalu Senanayake (ICML, 2024)

The Role of Predictive Uncertainty and Diversity in Embodied AI and Robot Learning. - Ransalu Senanayake (CoRR, 2024)

Fairness in Autonomous Driving: Towards Understanding Confounding Factors in Object Detection under Challenging Weather. - Bimsara Pathiraja; Caleb Liu; Ransalu Senanayake (CoRR, 2024)

Towards Adapting Reinforcement Learning Agents to New Tasks: Insights from Q-Values. - Ashwin Ramaswamy; Ransalu Senanayake (CoRR, 2024)

Explainable Concept Generation through Vision-Language Preference Learning. - Aditya Taparia; Som Sagar; Ransalu Senanayake (CoRR, 2024)

Trustworthy Conceptual Explanations for Neural Networks in Robot Decision-Making. - Som Sagar; Aditya Taparia; Harsh Mankodiya; Pranav Bidare; Yifan Zhou; Ransalu Senanayake (CoRR, 2024)

LLM-Assisted Red Teaming of Diffusion Models through "Failures Are Fated, But Can Be Faded". - Som Sagar; Aditya Taparia; Ransalu Senanayake (CoRR, 2024)

ExpressivityArena: Can LLMs Express Information Implicitly? - Joshua Tint; Som Sagar; Aditya Taparia; Kelly Raines; Bimsara Pathiraja; Caleb Liu; Ransalu Senanayake (CoRR, 2024)

RoboFail: Analyzing Failures in Robot Learning Policies. - Som Sagar; Ransalu Senanayake (CoRR, 2024)

MoSH: Modeling Multi-Objective Tradeoffs with Soft and Hard Bounds. - Edward Chen; Natalie Dullerud; Thomas Niedermayr; Elizabeth Kidd; Ransalu Senanayake; Pang Wei Koh; Sanmi Koyejo; Carlos Guestrin (CoRR, 2024)

Multiple Distribution Shift - Aerial (MDS-A): A Dataset for Test-Time Error Detection and Model Adaptation. - Noel Ngu; Aditya Taparia; Gerardo I. Simari; Mario A. Leiva; Ransalu Senanayake; Paulo Shakarian; Nathaniel D. Bastian; John Corcoran (AAAI Spring Symposia, 2025)

Multiple Distribution Shift - Aerial (MDS-A): A Dataset for Test-Time Error Detection and Model Adaptation. - Noel Ngu; Aditya Taparia; Gerardo I. Simari; Mario A. Leiva; Jack Corcoran; Ransalu Senanayake; Paulo Shakarian; Nathaniel D. Bastian (CoRR, 2025)

VLC Fusion: Vision-Language Conditioned Sensor Fusion for Robust Object Detection. - Aditya Taparia; Noel Ngu; Mario A. Leiva; Joshua Shay Kricheli; John Corcoran; Nathaniel D. Bastian; Gerardo I. Simari; Paulo Shakarian; Ransalu Senanayake (CoRR, 2025)

Consistency-based Abductive Reasoning over Perceptual Errors of Multiple Pre-trained Models in Novel Environments. - Mario A. Leiva; Noel Ngu; Joshua Shay Kricheli; Aditya Taparia; Ransalu Senanayake; Paulo Shakarian; Nathaniel D. Bastian; Jack Corcoran; Gerardo I. Simari (CoRR, 2025)

Strategic Vantage Selection for Learning Viewpoint-Agnostic Manipulation Policies. - Sreevishakh Vasudevan; Som Sagar; Ransalu Senanayake (CoRR, 2025)

PAC Bench: Do Foundation Models Understand Prerequisites for Executing Manipulation Policies? - Atharva Gundawar; Som Sagar; Ransalu Senanayake (CoRR, 2025)