Thoughts on generative models, video quality, and the intersection of perception and computation.
A long revision notebook for Research Scientist / GenAI loops focused on image generation, perceptual quality, and video processing: diffusion and flow models, transformer internals (attention variants, RoPE, KV cache), the text-to-image design space, evaluation metrics, color and HDR, classical CV, RL alignment, and the coding tier — all in one place.
Read more →Why classifier-free guidance breaks on flow models, and how a geometry-aware predictor-corrector fixes it — with a deep dive into text rendering quality and the adaptive schedule that makes it work.
Read more →An intuition-first deep dive into Rectified Flow with the core equations, geometric interpretation of trajectory straightness, and minimal PyTorch-style code snippets for training and sampling.
Read more →Why measuring quality in high dynamic range videos is fundamentally different from SDR, and what makes it one of the most challenging problems in perceptual quality research.
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