Tag
receptive-field
- Sep 6, 2026 Receptive Field Arithmetic and Effective Coverage How a unit back-propagates to the input positions that influence it, why the theoretical field overstates the real one, and how dilation and stride change the recurrence. deep learning
- May 17, 2024 Sliding-Window Attention and the Reach of a Stacked Local Window How a fixed-width window bounds per-layer cost while the stack multiplies its reach, what the reach formula predicts, and where the prediction fails because information cannot travel that far. deep learning
- Nov 4, 2023 Translational Weight Sharing and Feature Map Aliasing How a kernel applied at every position implements a translation-equivariant prior, what the stride lattice does to that guarantee, and where shift invariance actually breaks. deep learning
- May 5, 2022 Fixed-Window Models and the Hidden State They Cannot Represent Why a predictor restricted to the last k inputs cannot count, track nesting, or carry information past its window, and what a learned hidden state changes about that limit. deep learning