Reliable, minimal and scalable library for pretraining foundation and world models

This repository contains my research internship code at the University of Illinois Chicago under the supervision of Prof. Pedram Rooshenas.

This repository contains the implementations of our experiments and our approach presented in the paper: CoNCRA: A Convolutional Neural Network Code Retrieval Approach

Demo for Binding Text, Images, Graphs, and Audio for Music Representation Learning

A simple and efficient implementation of Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture (I-JEPA)

Code and Models for Binding Text, Images, Graphs, and Audio for Music Representation Learning