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### 🚀 The feature, motivation and pitch
Explainability has been an important component for users to probe model behavior, understand feature and structural importances, obtain new knowledge about t…
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## タイトル: TACE：腫瘍を考慮した反事実的説明生成
## リンク: https://arxiv.org/abs/2409.13045
## 概要:
深層学習は医療画像診断の精度と効率を大幅に向上させ、診断能力に革新をもたらしました。しかし、これらのAIモデルは「ブラックボックス」と呼ばれることが多く、その透明性の欠如は臨床現場における信頼性に対する懸念となっています。説明可能なAI…
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Hi,
First of all, thanks for a great product! I've been using Shapley-value-induced black-box model explanations for a few years now, starting with the work of Strumbelj and Kononenko (http://lkm.f…
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Hi Yanou, first of all, many thanks for these excellent counterfactual adaptations of existing explanation methods. I am using `SEDC_Explainer`, `ShapCounterfactual`, and `LimeCounterfactual` to expla…
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Hello
I want to train this repo on my own dataset but I have a problem with "oracle.pth" and "classifier.pt" ...
after taking a look at [guided-diffusion](https://github.com/openai/guided-diffusio…
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Operation
Terminals / Prompts
Action
Description
Tools
Status
nlpattribute
nlpattribute token | phrase | sentence {classes}
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Do you have any method for seeing which feature has the most importance/changeability power in a counterfactual? (Which features do more to move the counterfactual towards the decision boundary)
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Greetings!
I would like to visualize the counterfactuals found by VeriX. In the "VeriX" class, "get_explanation" function, I set the "plot_counterfactual" argument to true. The resulting counterfac…
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Hi, I was wondering if DiCE works with continuous variables such as time-series data or not.
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Hi, I trained an LSTM model using the feature vectors extracted from the data recorded by the students. I want to use DiCE to generate counterfactuals on the test set data, but I haven't found them. I…