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Found 9 papers, 5 papers with code
ADAPTER-RL: Adaptation of Any Agent using Reinforcement Learning
Deep Reinforcement Learning (DRL) agents frequently face challenges in adapting to tasks outside their training distribution, including issues with over-fitting, catastrophic forgetting and sample inefficiency.
Joint Dense-Point Representation for Contour-Aware Graph Segmentation
We present a novel methodology that combines graph and dense segmentation techniques by jointly learning both point and pixel contour representations, thereby leveraging the benefits of each approach.
3D Coronary Vessel Reconstruction from Bi-Plane Angiography using Graph Convolutional Networks
X-ray coronary angiography (XCA) is used to assess coronary artery disease and provides valuable information on lesion morphology and severity.
Partial advantage estimator for proximal policy optimization
Estimation of value in policy gradient methods is a fundamental problem.
Joint action loss for proximal policy optimization
Instead, for each sub-action we calculate the loss separately, which is less prone to clipping during updates thereby making better use of samples.
Classification of genetic variants using machine learning
Recent advances in genomic sequencing technology have resulted in an abundance of genome sequence data.
PROPEL: Probabilistic Parametric Regression Loss for Convolutional Neural Networks
We propose a PRObabilistic Parametric rEgression Loss (PROPEL) that facilitates CNNs to learn parameters of probability distributions for addressing probabilistic regression problems.
Fully Automatic Segmentation and Objective Assessment of Atrial Scars for Longstanding Persistent Atrial Fibrillation Patients Using Late Gadolinium-Enhanced MRI
In this study, we proposed a novel fully automatic pipeline to achieve an accurate and objective atrial scarring segmentation and assessment of LGE MRI scans for the AF patients.
Deep De-Aliasing for Fast Compressive Sensing MRI
Fast Magnetic Resonance Imaging (MRI) is highly in demand for many clinical applications in order to reduce the scanning cost and improve the patient experience.
