We introduce Chronos, a simple yet effective framework for pretrained probabilistic time
series models. Chronos tokenizes time series values using scaling and quantization into a …

Demand forecasting is an important task for retailers as it is required for various operational
decisions. One key challenge is to forecast demand on special days that are subject to vastly …

Diabetic retinopathy is one of the most threatening complications of diabetes that leads to
permanent blindness if left untreated. One of the essential challenges is early detection …

Diabetic retinopathy (DR) is the most common cause of blindness in middle-aged people. It
shows that an automatic image evaluation system is needed in the diagnosis of this disease …

Ordinal regression problems are those machine learning problems where the objective is to
classify patterns using a categorical scale which shows a natural order between the labels …

One of the most common types of cancer in men is prostate cancer (PCa). Biopsies guided
by biparametric magnetic resonance imaging (MRI) can aid PCa diagnosis. Previous works …

Multi-parametric MRI (mp-MRI) is considered the best non-invasive imaging modality for
diagnosing prostate cancer (PCa). However, mp-MRI for PCa diagnosis is currently limited …

We propose a novel algorithm for monocular depth estimation using relative depth maps.
First, using a convolutional neural network, we estimate relative depths between pairs of …

Ordinal regression (OR) is a crucial in machine learning. Usual assumption is that all
training instances are perfectly denoted. However, when this assumption does not hold, the …

In this work, we show that discretizing action space for continuous control is a simple yet
powerful technique for on-policy optimization. The explosion in the number of discrete …