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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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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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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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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…
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In chapter 1 you mention counterfactuals as equivalent to 0 the initial object.
But they have a lot more structure than 0.
An example taken from the 1973 book
[Counterfactuals](https://www.wiley.c…
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Hi, could you give a guideline for running the code, and how to deal with categorical data?
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here is a simple way to get started:
let's say the only things in our vocabulary are:
- A, B, E
- collided
- and
- not
some rules:
- the faster ball always collided with the slower ba…
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DiCE seems awesome. Thank you for your work on it!
I am trying to use DiCE with XGBoost/LightGBM but I am getting some unexpected behaviour. First and foremost, DiCE seems to "partially ignore" the…
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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…