This project aim to understad if a deep learning model is calibrated (average accuracy match average confident) using Reliability Diagram and perform a re-calibration by the training with Focal Loss.

A repository containing the deep learning-based geomagnetic storm forecasting model development codes

Conformal prediction R functions

An Uncertainty-Aware Pseudo-Label Selection Framework using Regularized Conformal Prediction

Code for my Bachelor's thesis "Drone image and video encoding and processing using machine learning"

Conformal Off-policy Prediction

Machine Learning with uncertainty quantification and interpretability

A serverless function is utilized to evaluate the divergence of a particular output from the established log-likelihood set by a language model. This function is designed to compute the log-likelihood per message. Subsequently, p-values are generated and used as a prediction interval to categorize, appropriately append, and sort LLM output

A graphical user interface (GUI) and web application to facilitate the usage of ENS-Score.

Machine Learning Assignment

Conformal Predictions using photonai

Conformal Prediction + Federated Learning

This is a small demo of Conformal Prediction given to Prof. Glenn Shafer's class in Feb-2018. Compares Conformal Prediction to plain Linear Regression using the Boston dataset from R

use cnn and conformal prediction to deal with mutilabel image issues

Prediction intervals for trees using conformal intervals. Docs at https://pitci.readthedocs.io/en/latest/

This repository contains jupyter notebooks providing an implementation of basic Machine Learning models for regression and classification.

Conformal Bayesian Computation (CBC). This paper summarizes the theoretical foundings of the CBC, as well as it applies to 2 use-cases: classification and regression.

Conformal Bayesian Computation with Stan and Numba.