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Found 5 papers, 1 papers with code
URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images
We present an integrated end-to-end pipeline that generates simulation scenes complete with articulated kinematic and dynamic structures from real-world images and use these for training robotic control policies.
Deep Representation Learning-Based Dynamic Trajectory Phenotyping for Acute Respiratory Failure in Medical Intensive Care Units
The study demonstrates the utility of our deep representation learning-based approach in unraveling phenotypes that reflect the heterogeneity in sepsis-induced ARF in terms of different mortality outcomes and severity.
Energy-Based Models for Cross-Modal Localization using Convolutional Transformers
We present a novel framework using Energy-Based Models (EBMs) for localizing a ground vehicle mounted with a range sensor against satellite imagery in the absence of GPS.
Model-based Behavioral Cloning with Future Image Similarity Learning
We present a visual imitation learning framework that enables learning of robot action policies solely based on expert samples without any robot trials.
Learning Real-World Robot Policies by Dreaming
Learning to control robots directly based on images is a primary challenge in robotics.
