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add eulaw with lime notebook (refs #756) #823

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merged 13 commits into from
Oct 11, 2024
Merged

add eulaw with lime notebook (refs #756) #823

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1ba1e62
add eulaw with lime notebook (refs #756)
cwmeijer Jun 19, 2024
6607639
add link and tutorial icon for eulaw (refs #756)
cwmeijer Aug 14, 2024
cde1700
Merge branch '829-no-more-torchtext-dependency' into 756-add-notebook…
cwmeijer Sep 19, 2024
a165038
adds EU law domain descriptions to help interpret the explainability …
kodymoodley Sep 24, 2024
2381edd
Merge branch 'main' into 756-add-notebook-for-eulaw
cwmeijer Oct 2, 2024
3f3e384
add links and doc references to eulaw notebook (refs #756)
cwmeijer Oct 2, 2024
f762245
Merge branch 'main' into 756-add-notebook-for-eulaw
cwmeijer Oct 9, 2024
aaf449c
remove tf upper boundary
cwmeijer Oct 9, 2024
05367cd
Update setup.cfg, put back tf upperlimit
cwmeijer Oct 9, 2024
c569994
Merge branch 'main' into 756-add-notebook-for-eulaw
cwmeijer Oct 9, 2024
2aa0f0e
add timeout length in the metadata of the eulaw notebook
cwmeijer Oct 10, 2024
7b9c965
fixing the correct main version of the downloader.py
elboyran Oct 10, 2024
e4980d8
adding the EU law case data location to the downloader.py
elboyran Oct 10, 2024
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23 changes: 12 additions & 11 deletions README.md
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Expand Up @@ -200,7 +200,7 @@ Explore the explanations of your trained model using the DIANNA dashboard (for n
_Dianna dashboard screenshot here_
<!-- <a href="https://github.com/dianna-ai/dianna/tree/main/dianna/dashboard" target="_blank">
<img width="1000" align="center" alt="Dianna dashboard screenshot" src="https://raw.githubusercontent.com/dianna-ai/dianna/main/dianna/dashboard/dashboard-screenshot.png">
</a>
</a>
-->

## Datasets
Expand Down Expand Up @@ -260,9 +260,10 @@ And here are links to notebooks showing how we created our models on the benchma

### Text

| Models | Generation |
| :---------------------------------------------------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [Movie reviews model](https://zenodo.org/record/5910598) | [Stanford sentiment treebank model generation](https://github.com/dianna-ai/dianna-exploration/blob/main/example_data/model_generation/movie_reviews/generate_model.ipynb) |
| Models | Generation |
|:---------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [Movie reviews model](https://zenodo.org/record/5910598) | [Stanford sentiment treebank model generation](https://github.com/dianna-ai/dianna-exploration/blob/main/example_data/model_generation/movie_reviews/generate_model.ipynb) |
| [Regalatory statement classifier](https://zenodo.org/record/8200001) | [EU-law regulatory-statement-classification](https://github.com/nature-of-eu-rules/regulatory-statement-classification) |

### Time series

Expand Down Expand Up @@ -306,13 +307,13 @@ Also [GradCAM](https://openaccess.thecvf.com/content_ICCV_2017/papers/Selvaraju_
Our goal is that the scientific community embrases XAI as a source for novel and unexplored perspectives on scientific problems.
Here, we offer [tutorials](./tutorials) on specific scientific use-cases of uisng XAI:

| Use-case (data) \ XAI | [RISE](http://bmvc2018.org/contents/papers/1064.pdf) | [LIME](https://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf) | [KernelSHAP](https://proceedings.neurips.cc/paper/2017/file/8a20a8621978632d76c43dfd28b67767-Paper.pdf) |
| :----------------------------------------------------------------| :----------------------------------------------------| :---------------------------------------------------------------------| :-------------------------------------------------------------------------------------------------------|
| Biology (Phytomorphology): Tree Leaves classification (images) | | ✅ | |
| Astronomy: Fast Radio Burst detection (timeseries) | ✅ | | |
| Land-atmosphere modeling: Latent heat flux prediction (tabular) | | | ✅ |
| Social sciences (text) | work in progress | ... |... |
| Climate | planned | ... | ... |
| Use-case (data) \ XAI | [RISE](http://bmvc2018.org/contents/papers/1064.pdf) | [LIME](https://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf) | [KernelSHAP](https://proceedings.neurips.cc/paper/2017/file/8a20a8621978632d76c43dfd28b67767-Paper.pdf) |
|:-------------------------------------------------------------------|:-----------------------------------------------------| :---------------------------------------------------------------------| :-------------------------------------------------------------------------------------------------------|
| Biology (Phytomorphology): Tree Leaves classification (images) | | ✅ | |
| Astronomy: Fast Radio Burst detection (timeseries) | ✅ | | |
| Land-atmosphere modeling: Latent heat flux prediction (tabular) | | | ✅ |
| Social sciences: EU-law regulatory statement classification (text) | | ✅ | |
| Climate | planned | ... | ... |

## Reference documentation

Expand Down
4 changes: 4 additions & 0 deletions dianna/utils/downloader.py
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Expand Up @@ -59,6 +59,10 @@
"doi:10.5281/zenodo.10656613/apertif_frb_dynamic_spectrum_model.onnx",
"sha256:3c87db3c6257d7f251a7bdceb3197d5bb482b8edc19870219fb7ca7c204dd257"
],
"inlegal_bert_xgboost_classifier.json": [
"doi:10.5281/zenodo.8200001/inlegal_bert_xgboost_classifier.json",
"68a672f29aac4a19c404c24f4c5da82a1ce7f704ccce701b0a1073c63730e127"
],
"stemmus_scope_emulator_model_LEtot.onnx": [
"doi:10.5281/zenodo.12623256/stemmus_scope_emulator_model_LEtot.onnx",
"sha256:8c8f34ad5a2c519b1f3c67a4eb0c645c96cac1de166277bfb24e7887c2ce83be"
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3 changes: 3 additions & 0 deletions docs/tutorials/9-lime_text_eulaw.nblink
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@@ -0,0 +1,3 @@
{
"path": "../../tutorials/explainers/LIME/lime_text_eulaw.ipynb"
}
3 changes: 3 additions & 0 deletions setup.cfg
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Expand Up @@ -112,6 +112,9 @@ notebooks =
torch
torchvision
ipywidgets
freetype-py
transformers
xgboost

[options.entry_points]
console_scripts =
Expand Down
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