Implementation of the Pseudo-Projector, application of multigrid methods to deep neural networks, by Vitaly Bulgakov
Project description
Pseudo-projector
Implementation of the pseudo projector proposed by Vitaly Bulgakov during his work applying transformers to medical records at Mass General Brigham Hospital
Install
$ pip install pseudo-projector
Usage
import torch
from pseudo_projector import PseudoProjector
proj = PseudoProjector(dim = 64, dim_lowrank = 16)
feats = torch.randn(1, 8, 1024, 64) # any number of preceding dimensions
out = proj(feats)
assert feats.shape == out.shape
With the learned blending of original features with the coarsened ones
import torch
from pseudo_projector import PseudoProjector
proj = PseudoProjectorWithResidual(dim = 64, dim_lowrank = 16, learned_alpha = True)
feats = torch.randn(1, 8, 1024, 64) # any number of preceding dimensions
out = proj(feats)
assert feats.shape == out.shape
Citations
@misc{bulgakov2026correctiontransformerbasedmodelssmoothing,
title = {Correction of Transformer-Based Models with Smoothing Pseudo-Projector},
author = {Vitaly Bulgakov},
year = {2026},
eprint = {2603.09815},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2603.09815},
}
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