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Large Language Models (LLMs) have brought a new twist to the way we think about training algorithms. While traditional Supervised Learning (SL) and Reinforcement Learning (RL) migh...

Most of us, whether consciously or not, use Maximum Likelihood Estimation (MLE) in our daily machine learning workflows. When you’re training a model to predict labels in a supervi...

In this post, I'll walk you through the process of training a Graph Convolutional Network (GCN) for edge classification, a common task in graph based machine learning applications....

The project is the core of my PhD work. It was heavily inspired by the cognitive science theories, such as the ones from . It's about developing agents equipped with human like ext...