DeformerNet: A Deep Learning Approach to 3D Deformable Object Manipulation. - Bao Thach; Alan Kuntz; Tucker Hermans (CoRR, 2021)

Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Clouds. - Bao Thach; Brian Y. Cho; Alan Kuntz; Tucker Hermans (ICRA, 2022)

DeformerNet: Learning Bimanual Manipulation of 3D Deformable Objects. - Bao Thach; Brian Y. Cho; Tucker Hermans; Alan Kuntz (CoRR, 2023)

DefGoalNet: Contextual Goal Learning from Demonstrations for Deformable Object Manipulation. - Bao Thach; Tanner Watts; Shing-Hei Ho; Tucker Hermans; Alan Kuntz (ICRA, 2024)

Reward Learning from Suboptimal Demonstrations with Applications in Surgical Electrocautery. - Zohre Karimi; Shing-Hei Ho; Bao Thach; Alan Kuntz; Daniel S. Brown (ISMR, 2024)

Generative LiDAR Editing with Controllable Novel Object Layouts. - Shing-Hei Ho; Bao Thach; Minghan Zhu (CoRR, 2024)

Accounting for Hysteresis in the Forward Kinematics of Nonlinearly-Routed Tendon-Driven Continuum Robots via a Learned Deep Decoder Network. - Brian Y. Cho; Daniel S. Esser; Jordan Thompson; Bao Thach; Robert J. Webster III; Alan Kuntz (IEEE Robotics Autom. Lett., 2024)

DefFusionNet: Learning Multimodal Goal Shapes for Deformable Object Manipulation via a Diffusion-based Probabilistic Model. - Bao Thach; Siyeon Kim; Britton Jordan; Mohanraj Devendran Shanthi; Tanner Watts; Shing-Hei Ho; James M. Ferguson; Tucker Hermans; Alan Kuntz (CoRR, 2025)