Supportive Actions for Manipulation in Human-Robot Coworker Teams. - Shray Bansal; Rhys Newbury; Wesley P. Chan; Akansel Cosgun; Aimee Allen; Dana Kulic; Tom Drummond; Charles Isbell (IROS, 2020)

Learning to Take Good Pictures of People with a Robot Photographer. - Rhys Newbury; Akansel Cosgun; Mehmet Köseoglu; Tom Drummond (IROS, 2020)

Learning to Place Objects onto Flat Surfaces in Human-Preferred Orientations. - Rhys Newbury; Kerry He; Akansel Cosgun; Tom Drummond (CoRR, 2020)

Automated Iterative Training of Convolutional Neural Networks for Tree Skeleton Segmentation. - Keenan Granland; Rhys Newbury; David Ting; Chao Chen (CoRR, 2020)

Demonstrating Cloth Folding to Robots: Design and Evaluation of a 2D and a 3D User Interface. - Benjamin Waymouth; Akansel Cosgun; Rhys Newbury; Tin Tran; Wesley P. Chan; Tom Drummond; Elizabeth A. Croft (RO-MAN, 2021)

Semantic segmentation for partially occluded apple trees based on deep learning. - Zijue Chen; David Ting; Rhys Newbury; Chao Chen (Comput. Electron. Agric., 2021)

Tabletop Object Rearrangement: Team ACRV's Entry to OCRTOC. - Zheyu Zhang; Rhys Newbury; Kerry He; Steven Martin; Gavin Suddrey; Jun Kwan; Peter Corke; Akansel Cosgun (CoRR, 2021)

Learning to Place Objects Onto Flat Surfaces in Upright Orientations. - Rhys Newbury; Kerry He; Akansel Cosgun; Tom Drummond (IEEE Robotics Autom. Lett., 2021)

Object-Independent Human-to-Robot Handovers Using Real Time Robotic Vision. - Patrick Rosenberger; Akansel Cosgun; Rhys Newbury; Jun Kwan; Valerio Ortenzi; Peter Corke; Manfred Grafinger (IEEE Robotics Autom. Lett., 2021)

Decentralized Multi-Agent Pursuit Using Deep Reinforcement Learning. - Cristino de Souza; Rhys Newbury; Akansel Cosgun; Pedro Castillo; Boris Vidolov; Dana Kulic (IEEE Robotics Autom. Lett., 2021)

In-Hand Gravitational Pivoting Using Tactile Sensing. - Jason Toskov; Rhys Newbury; Mustafa Mukadam; Dana Kulic; Akansel Cosgun (CoRL, 2022)

Integrating High-Resolution Tactile Sensing into Grasp Stability Prediction. - Lachlan Chumbley; Morris Gu; Rhys Newbury; Jürgen Leitner; Akansel Cosgun (CRV, 2022)

Visualizing Robot Intent for Object Handovers with Augmented Reality. - Rhys Newbury; Akansel Cosgun; Tysha Crowley-Davis; Wesley P. Chan; Tom Drummond; Elizabeth A. Croft (RO-MAN, 2022)

Detecting occluded Y-shaped fruit tree segments using automated iterative training with minimal labeling effort. - Keenan Granland; Rhys Newbury; Zijue Chen; David Ting; Chao Chen (Comput. Electron. Agric., 2022)

HOB-CNN: Hallucination of Occluded Branches with a Convolutional Neural Network for 2D Fruit Trees. - Zijue Chen; Keenan Granland; Rhys Newbury; Chao Chen (CoRR, 2022)

Comparing Subjective Perceptions of Robot-to-Human Handover Trajectories. - Alexander Calvert; Wesley P. Chan; Tin Tran; Sara Sheikholeslami; Rhys Newbury; Akansel Cosgun; Elizabeth A. Croft (CoRR, 2022)

Visibility Maximization Controller for Robotic Manipulation. - Kerry He; Rhys Newbury; Tin Tran; Jesse Haviland; Ben Burgess-Limerick; Dana Kulic; Peter Corke; Akansel Cosgun (IEEE Robotics Autom. Lett., 2022)

Deep Learning Approaches to Grasp Synthesis: A Review. - Rhys Newbury; Morris Gu; Lachlan Chumbley; Arsalan Mousavian; Clemens Eppner; Jürgen Leitner; Jeannette Bohg; Antonio Morales; Tamim Asfour; Danica Kragic; Dieter Fox; Akansel Cosgun (IEEE Trans. Robotics, 2023)

A Review of Differentiable Simulators. - Rhys Newbury; Jack Collins; Kerry He; Jiahe Pan; Ingmar Posner; David Howard 001; Akansel Cosgun (IEEE Access, 2024)

Carefully Structured Compression: Efficiently Managing StarCraft II Data. - Bryce Ferenczi; Rhys Newbury; Michael G. Burke; Tom Drummond (CoRR, 2024)

INSPIRE-GNN: Intelligent Sensor Placement to Improve Sparse Bicycling Network Prediction via Reinforcement Learning Boosted Graph Neural Networks. - Mohit Gupta; Debjit Bhowmick; Rhys Newbury; Meead Saberi; Shirui Pan; Ben Beck (CoRR, 2025)

Why Heuristic Weighting Works: A Theoretical Analysis of Denoising Score Matching. - Juyan Zhang; Rhys Newbury; Xinyang Zhang; Tin Tran; Dana Kulic; Michael G. Burke (CoRR, 2025)

POSGGym: a library for decision-theoretic planning and learning in partially observable, multi-agent environments. - Jonathon Schwartz; Rhys Newbury; Dana Kulic; Hanna Kurniawati (Auton. Agents Multi Agent Syst., 2025)