Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

Deep Neural Networks for Call Of Duty Modern Warfare 2019

🍊 📦 Frequent itemsets and association rules mining for Orange 3.

Code for "Unsupervised Adaptation for Deep Stereo" - ICCV17

Generate a Work Breakdown Structure (WBS) report from a markdown file. A tool that improves software development estimates.

Minimal A/B Testing Library in PHP

Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"

Supplementary material to reproduce "Multivariate Deep Evidential Regression"

Magnitude of the Effect - An Effect Size and CI calculator

🧠 A simple, fully documented neural network library created for educational purposes, heavily inspired by the `ai` package.

An open source initiative to help students prepare for HR interviews.

Source code of "Calibrating Large Language Models Using Their Generations Only", ACL2024

A suite of tests to assess attention faithfulness for explainability

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

A comprehensive module used to calculate the high bound, low bound, and center of a Wilson score interval.

I implemented the reinforcement learning based model Upper Confidence Bound in both Python and R

My Gateway to crack DSA

A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets

Code for paper "Factual Confidence of LLMs: on Reliability and Robustness of Current Estimators"

Implementation of the Apriori algorithm in python, to generate frequent itemsets and association rules. Experimentation with different values of confidence and support values.