#generative models

2025-08-13

#deep learning #transformers #LLM #generative models

Notes on the Transformer architecture: attention mechanisms, multi-head attention, positional encoding, and encoder/decoder layers with PyTorch implementations.

✍️ Worth to read papers

2025-07-15

#deep learning #papers #generative models #math

A compilation of interesting papers I enjoyed reading, including I-Con, Denoising Diffusion Probabilistic Models, and SpiRobs.

🌀 Diffusion Models Notes

2025-06-13

#deep learning #diffusion models #generative models

Notes on the mathematical foundations of diffusion models, including the noising process, denoising process, loss function, and training/generation loops.