My blogs
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Statistics & Inference (Theory)
Modeling
Systems & Infrastructure
Interpretability & Understanding
AI for Science (Domain)
Agents & Scientific Workflows
Notes coming later.
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Explainable AI (XAI) and Model Interpretability (SHAP, Integrated Gradients, and Sparse Autoencoders)
A future-me-friendly toolbox of interpretability methods: feature attribution (Shapley/SHAP, Integrated Gradients), perturbation tests, and representation-level methods like Sparse Autoencoders.
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Diffusion Language Models Deep Dive (Part 1: Method)
This post explains general development of diffusion language models (DLMs), including Discrete Diffusion, and Simple and Effective Masked Diffusion Language Models.
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Minimum Math Review for Diffusion Language Models
Diffusion Objective, Variational Inference, and KL
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More on Parallelism
More on Sharding and Parallelism
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Transformer, Scaling, and Efficiency
Summary Notes on Catching Up