A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

PyTorch implementation of a VAE-based generative classifier, as well as other class-incremental learning methods that do not store data (DGR, BI-R, EWC, SI, CWR, CWR+, AR1, the "labels trick", SLDA).

PyTorch implementation of various distillation approaches for continual learning of Diffusion Models.

Solving catastrophic forgetting with Recursive Time architecture, Active Sleep (generative replay), and Temporal LoRA. Proving the "Lazarus Effect" in neural networks.

SCalable Continual Learning - An experimental machine learning framework for the investigation of continual learning algorithms.

🧠 Explore notebook codes for the Deep Learning course at Sapienza Università di Roma, enhancing your understanding of applied AI techniques.