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

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

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

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

[CVPR 2026] FLAC: Few-Shot Acoustic Synthesis with Flow Matching. FLAC enables RIR generation in novel scenes using only one-shot acoustic observation. The repository also provides AGREE, a joint embedding space for RIRs and room geometry, designed to evaluate the geometric consistency of RIR synthesis models.

PyTorch code and models for VJEPA2 self-supervised learning from video.