🚀 Projects

The increasing depth and width of neural networks improve accuracy but also raise hardware requirements and slow down inference. This project proposes a distillation loss function that enables immediate weight and activation pruning on the student model after distillation.

This project designed a JEPA architecture model with CNN and MLPs as encoder and predictor. The main task is to predict the trajectory of an object in an environment with wall and door.