Reinforcement learning has achieved great success in game scenarios, with RL agents beating human competitors in such games as Go and poker. Distributional reinforcement learning, in particular, has ...

Radiomics involves the study of tumor images to identify quantitative markers explaining cancer heterogeneity. The predominant approach is to extract hundreds to thousands of image features, including ...

import pandas as pd import numpy as np df = pd.DataFrame(data={'a': np.arange(100), 'b': np.arange(100),}) df = df.quantile([0.2, 0.5, 0.8], axis=1) Using DataFrame.quantile over axis=1 with multiple ...

Distributional Reinforcement Learning (RL) differs from traditional RL in that, rather than the expectation of total returns, it estimates distributions and has achieved state-of-the-art performance ...

Estimating the conditional quantiles of outcome variables of interest is frequent in many research areas, and quantile regression is foremost among the utilized methods. The coefficients of a quantile ...

Glioblastoma multiforme (GBM) is the most common and most aggressive cancer that begins within the brain. Most GBM diagnoses are made by medical imaging such as magnetic resonance imaging (MRI), where ...

Quantile regression(QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive ...

This paper considers a linear triangular simultaneous equations model with conditional quantile restrictions. The paper adjusts for endogeneity by adopting a control function approach and presents a ...

Department of Biostatistics & Bioinformatics, Rollins School of Public Health, Winship Cancer Institute, Atlanta, USA. Department of Biostatistics and Computational Biology University of Rochester, ...