Ml

Write-up explaining my implementation of monotonic attention using a probabilistic graphical model.

A short, hand-wavy explainer for the mathematical intuition behind faster attention mechanisms.

Working out the math for streaming convolutions.

An accessible introduction to diffusion and flow matching models. This post aims to be both complete and easy-to-follow as a reference for implementing diffusion models yourself.

A reference collection of fast attention implementations.

In-depth explanation of the math behind the RWKV model, with PyTorch implementations, plus a discussion of numerical stability.

A collection of my ideas relating to robotics pre-training.

A comparison of Hidden Markov Models and Conditional Random Fields, two kinds of probabilistic graphical models.

A demo of how to code the Viterbi algorithm in Numpy.

A short post and script regarding using Gensim Word2Vec embeddings in Keras, with example code.

Building on the Recurrent RBM for sequence modeling. This post relates to what I am doing for my Master's thesis.

An in-depth introduction to using Keras for language modeling; word embedding, recurrent and convolutional neural networks, attentional RNNs, and similarity metrics for vector embeddings.

A quick introduction to using Theano for deep learning, from the bare-bones to a full neural network.