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Blog · Seungheon Doh

  • Sep 7, 2026
    Agents and Reinforcement LearningArticle

    From an agent's execution loop to trajectories and returns, REINFORCE, PPO and GRPO, the token-level loss, long-horizon credit assignment, distillation, and reproducible evaluation.

  • Aug 17, 2026
    Self-Supervised Learning and CollapseArticle

    How self-supervised learning collapses, from the obvious to the hidden.

  • Aug 16, 2026
    Interactive Stochastic Differential EquationsStudy

    Random walks and Brownian motion, stochastic processes and the Markov property, Itô calculus and SDEs, and finally the Fokker–Planck equation and the probability flow ODE.

  • Aug 16, 2026
    Interactive Differential EquationsStudy

    ODEs and their numerical solvers — direction fields, initial value problems, phase portraits, Euler and Runge–Kutta, and numerical stability — then PDEs: the transport, continuity and diffusion equations.

  • Aug 8, 2026
    Interactive CalculusStudy

    Functions, limits, derivatives and the chain rule, Taylor expansion and integrals, then partial derivatives, the gradient, Jacobian, Hessian, vector fields, divergence and the Laplacian.

  • Jul 30, 2026
    Interactive Information TheoryStudy

    Self-information, entropy and coding length, cross-entropy and KL divergence, mutual information, and the losses built on them — cross-entropy, perplexity, the ELBO, and InfoNCE.

  • Jul 23, 2026
    Interactive ProbabilityStudy

    Random variables, joint and conditional distributions, expectation, the distributions machine learning actually uses, and the road from likelihood to NLL, Bayes' rule, and MAP.

  • Jul 14, 2026
    Interactive Linear AlgebraStudy

    Vectors, inner products, eigenvalues, the four fundamental subspaces, change of basis, and PyTorch einsum/permute/view/reshape.

© 2026 Seungheon Doh