SkillAgentSearch skills...

SGPA

Example code of Sparse Gaussian Process Attention (ICLR 2023)

Install / Use

/learn @chenw20/SGPA
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Sparse Gaussian Process Attention

This is an example code for the paper titled Calibrating Transformers via Sparse Gaussian Processes (ICLR 2023)

This code implememts SGPA on CIFAR10 and IMDB datasets.

To use this code: simply run train_cifar.py or train_imdb.py

The IMDB dataset can be downloaded here

Dependencies:

  • Python - 3.8
  • Pytorch - 1.10.2
  • numpy - 1.22.4
  • einops - 0.4.1
  • pandas - 1.4.3
  • transformers - 4.18.0

Citing the paper (bib)

@inproceedings{chen2023calibrating,
  title = {Calibrating Transformers via Sparse Gaussian Processes},
  author = {Chen, Wenlong and Li, Yingzhen},
  booktitle = {International Conference on Learning Representations},
  year = {2023}
}

Related Skills

View on GitHub
GitHub Stars26
CategoryDevelopment
Updated1mo ago
Forks4

Languages

Python

Security Score

75/100

Audited on Feb 18, 2026

No findings