38 citations · 91 across the 6 of their papers we have counts for
8 papers
Robust Temporal Ensembling for Learning with Noisy Labels
Abel Brown, Benedikt Schifferer, Robert DiPietro
Successful training of deep neural networks with noisy labels is an essential capability as most real-world datasets contain some amount of mislabeled data. Left unmitigated, label…
Automated Surgical Activity Recognition with One Labeled Sequence
Robert DiPietro, Gregory D. Hager
Prior work has demonstrated the feasibility of automated activity recognition in robot-assisted surgery from motion data. However, these efforts have assumed the availability of a…
Unsupervised Learning for Surgical Motion by Learning to Predict the Future
Robert DiPietro, Gregory D. Hager
We show that it is possible to learn meaningful representations of surgical motion, without supervision, by learning to predict the future. An architecture that combines an RNN enc…
Long Short-Term Memory Kalman Filters:Recurrent Neural Estimators for Pose Regularization
Huseyin Coskun, Felix Achilles, Robert DiPietro +2
One-shot pose estimation for tasks such as body joint localization, camera pose estimation, and object tracking are generally noisy, and temporal filters have been extensively used…
Analyzing and Exploiting NARX Recurrent Neural Networks for Long-Term Dependencies
Robert DiPietro, Christian Rupprecht, Nassir Navab +1
Recurrent neural networks (RNNs) have achieved state-of-the-art performance on many diverse tasks, from machine translation to surgical activity recognition, yet training RNNs to c…
Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses
Christian Rupprecht, Iro Laina, Robert DiPietro +4
Many prediction tasks contain uncertainty. In some cases, uncertainty is inherent in the task itself. In future prediction, for example, many distinct outcomes are equally valid. I…
Recognizing Surgical Activities with Recurrent Neural Networks
Robert DiPietro, Colin Lea, Anand Malpani +5
We apply recurrent neural networks to the task of recognizing surgical activities from robot kinematics. Prior work in this area focuses on recognizing short, low-level activities,…
Determining Magnetic Nanoparticle Size Distributions from Thermomagnetic Measurements
R. S. DiPietro, H. G. Johnson, S. P. Bennett +3
Thermomagnetic measurements are used to obtain the size distribution and anisotropy of magnetic nanoparticles. An analytical transformation method is described which utilizes tempe…