Decoding LoRA: A Comprehensive Summary on Low-Rank Adaptation
A summary of LoRA: how low-rank adaptation fine-tunes large language models by training small update matrices instead of the full weights.
Latest posts
Comparing Sequence-to-Sequence Decoders: With and Without Attention
A hands-on comparison of sequence-to-sequence decoders with and without attention, going beyond a standard code walkthrough.
Note: Derivation of Normal Bayesian Test
A derivation of the Normal Bayesian test for hypothesis testing.
Capturing Dominant Spatial Patterns with Two-Dimensional Locations Using SpatPCA
Using SpatPCA in R to capture the most dominant spatial pattern from data on two-dimensional locations, step by step.
Apply SpatPCA to Capture the Dominant Spatial Pattern with One-Dimensional Locations
A SpatPCA tutorial on recovering the dominant spatial pattern from one-dimensional locations, and how it holds up as the signal-to-noise ratio changes.