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Balázs Gyenes

6 accepted papers

2026

Fourier Features Let Agents Learn High Precision Policies with Imitation Learning

ICML 2026poster

Various 3D modalities have been proposed for high-precision imitation learning tasks to compensate for the short-comings of RGB-only policies. Modalities that explicitly represent positions in Cartesian space, such as most point cloud encoder architectures, have an inherent advantage over purely ima…

Cited by 0SourcecodeScholar
2025

AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution Prediction

NeurIPS 2025poster

The cost and accuracy of simulating complex physical systems using the Finite Element Method (FEM) scales with the resolution of the underlying mesh. Adaptive meshes improve computational efficiency by refining resolution in critical regions, but typically require task-specific heuristics or cumbers…

Cited by 0SourcecodeScholar
2025

Point Cloud Segmentation for Autonomous Clip Positioning in Laparoscopic Cholecystectomy on a Phantom

RA-L 2025

High-risk applications in robotics, such as robot-assisted surgery, present unique challenges. These systems must be both highly precise and interpretable in order to be deployed in environments with very low tolerance for error or unsafe exploration. We present the first robotic system to demonstra

Cited by 0SourcecodeScholar
2025

PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning

NeurIPS 2025poster

Robotic manipulation systems benefit from complementary sensing modalities, where each provides unique environmental information. Point clouds capture detailed geometric structure, while RGB images provide rich semantic context. Current point cloud methods struggle to capture fine-grained detail, es…

Cited by 0SourcecodeScholar
2023

Sim-to-Real Transfer for Visual Reinforcement Learning of Deformable Object Manipulation for Robot-Assisted Surgery

RA-L 2023

Automation holds the potential to assist surgeons in robotic interventions, shifting their mental work load from visuomotor control to high level decision making. Reinforcement learning has shown promising results in learning complex visuomotor policies, especially in simulation environments where m

Cited by 82SourceScholar
2021

Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning

IROS 2021poster

Cognitive cooperative assistance in robot-assisted surgery holds the potential to increase quality of care in minimally invasive interventions. Automation of surgical tasks promises to reduce the mental exertion and fatigue of surgeons. In this work, multi-agent reinforcement learning is demonstrate…

Cited by 21SourceScholar