Implementation for "Conditional entropy minimization principle for learning domain invariant representation features"

Last update: Nov 02, 2022

Overview

Implementation for "Conditional entropy minimization principle for learning domain invariant representation features".

The code is reproduced from this repo at https://github.com/ahujak/IB-IRM.

Please see the guideline for running in each sub-dataset folder.

Requirements:

torch 1.6.0
torchvision 0.7.0
numpy 1.19.1
tqdm 4.41.1

Owner

GitHub Repository

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Implementation for "Conditional entropy minimization principle for learning domain invariant representation features"

Related tags

Overview

Owner

competitions-v2

[CVPR 2021] Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion

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Implementation for "Conditional entropy minimization principle for learning domain invariant representation features"

Related tags

Overview

Owner

competitions-v2

[CVPR 2021] Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion

[CVPR 21] Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2021.

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Fully Automatic Page Turning on Real Scores

Sequential Model-based Algorithm Configuration

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

Cockpit is a visual and statistical debugger specifically designed for deep learning.

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