Search Results for author:
Found 6 papers, 4 papers with code
ASID: Active Exploration for System Identification in Robotic Manipulation
In this work, we propose a learning system that can leverage a small amount of real-world data to autonomously refine a simulation model and then plan an accurate control strategy that can be deployed in the real world.
Modality-invariant Visual Odometry for Embodied Vision
Our model outperforms previous methods while training on only a fraction of the data.
Dimensionality Reduction and Prioritized Exploration for Policy Search
Black-box policy optimization is a class of reinforcement learning algorithms that explores and updates the policies at the parameter level.
Scalable 3D Semantic Segmentation for Gun Detection in CT Scans
With the increased availability of 3D data, the need for solutions processing those also increased rapidly.
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations
In this work, we show the advantages of prototype representations for understanding and revising the latent space of neural concept learners.
Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation
Deep learning for medical imaging suffers from temporal and privacy-related restrictions on data availability.
