Tensorflow implementations of ordinal regression

Undergraduate final project: Ordinal Clasification with Residual Networks for the Adience dataset.

Generic implementation for Generalized Linear Models including Logistic, Poisson and Ordinal Regression for Classification purposes

A Python Implementation of Kernel Extreme Learning Machine for Ordinal Regression

PyTorch implementation of Deep Ordinal Regression Network for Monocular Depth Estimation

Code for the paper `Non-parametric Uni-modality Constraints for Deep Ordinal Classification`.

Reproduction of the CVPR 2020 paper - Self-supervised monocular trained depth estimation using self-attention and discrete disparity volume

Rank Consistent Ordinal Regression for Neural Networks with Application to Age Estimation

Ordinal regression models in PyTorch

Ordinal Losses for Classification of Cervical Cancer Risk

Code for MICCAI 2023 publication: SCOL: Supervised Contrastive Ordinal Loss for Abdominal Aortic Calcification Scoring on Vertebral Fracture Assessment Scans

Ordinal regression in Python

[ECCV 2024] Teach CLIP to Develop a Number Sense for Ordinal Regression

CORAL and CORN implementations for ordinal regression with deep neural networks.

Deep learning pipeline for knee osteoarthritis severity assessment from X-rays using ordinal classification.

Tensorflow Keras implementation of ordinal regression using consistent rank logits (CORAL) by Cao et al. (2019)

Ordinal regression and mediation analysis examining the gap between AI adoption and advocacy among K-12 educators. Part 3 of a three-paper series using JASP and Python. N=189 teachers in Jordan.