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Sarah Osentoski

4 accepted papers

2025

Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework

NeurIPS 2025poster

We introduce copresheaf topological neural networks (CTNNs), a powerful unifying framework that encapsulates a wide spectrum of deep learning architectures, designed to operate on structured data, including images, point clouds, graphs, meshes, and topological manifolds. While deep learning has prof…

Cited by 0SourceScholar
2015

Active articulation model estimation through interactive perception

ICRA 2015poster

We introduce a particle filter-based approach to representing and actively reducing uncertainty over articulated motion models. The presented method provides a probabilistic model that integrates visual observations with feedback from manipulation actions to best characterize a distribution of possi…

Cited by 113SourceScholar
2015

Online Bayesian changepoint detection for articulated motion models

ICRA 2015poster

We introduce CHAMP, an algorithm for online Bayesian changepoint detection in settings where it is difficult or undesirable to integrate over the parameters of candidate models. CHAMP is used in combination with several articulation models to detect changes in articulated motion of objects in the wo…

Cited by 59SourceScholar
2015

Robot Web Tools: Efficient messaging for cloud robotics

IROS 2015poster

Since its official introduction in 2012, the Robot Web Tools project has grown tremendously as an open-source community, enabling new levels of interoperability and portability across heterogeneous robot systems, devices, and front-end user interfaces. At the heart of Robot Web Tools is the rosbridg…

Cited by 125SourceScholar