inseq-team/inseq

Interpretability for sequence generation models 🐛 🔍

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kotiyalanurag/Exploring-Data-Augmentation-Methods-through-Attribution

Code for my Master Thesis titled "Exploring Data Augmentation Methods through Attribution".

Language: Python - Size: 2.87 MB - Last synced at: 13 days ago - Pushed at: 13 days ago - Stars: 0 - Forks: 0

cdpierse/transformers-interpret

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

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FilippoMB/Tutorial_GNN_explainability

This in an introduction to PyTorch Geometric, the deep learning library for Graph Neural Networks, and to interpretability tools for analyzing the decision process of a GNN.

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jihyeonseong/SAI-board-by-streamlit

Cyber Security AI Dashboard

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luispky/XAI-RAI-UniTS

Repository with the project of the Explainable and Reliable Artificial Intelligence course at UniTS (2024-2025).

Language: Python - Size: 76 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

k-forghani/pytorch-workshop

PyTorch Beginner Workshop (Brad Heintz)

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CECNL/XBrainLab

We introduce XBrainLab, an open-source user-friendly software, for accelerated interpretation of neural patterns from EEG data based on cutting-edge computational approach.

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R-N/covid-forecasting-joint-learning

COVID-19 forecasting model for East Java cities using Joint Learning

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DFKI-NLP/thermostat

Collection of NLP model explanations and accompanying analysis tools

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NajdBinrabah/Deep-Learning-with-PyTorch-and-Captum

This project classifies smoking images using VGG19 with data augmentation, and Captum for model explainability, identifying key features per prediction.

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braindatalab/xai-tris

XAI-Tris

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the-ahuja-lab/Odorify-webserver

OdoriFy is an open-source tool with multiple prediction engines. This is the source code of the webserver.

Language: Python - Size: 57 MB - Last synced at: 3 months ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 1

TannerGilbert/Model-Interpretation

Overview of different model interpretability libraries.

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LennardZuendorf/thesis-files

Collection of associated files for my bachelor thesis

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esceptico/toxic

End-to-end toxic Russian comment classification

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copenlu/ALPS_2021

XAI Tutorial for the Explainable AI track in the ALPS winter school 2021

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dg1223/explainable-ai

Model interpretability for Explainable Artificial Intelligence

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richouzo/hate-speech-detection-survey

Trained Neural Networks (LSTM, HybridCNN/LSTM, PyramidCNN, Transformers, etc.) & comparison for the task of Hate Speech Detection on the OLID Dataset (Tweets).

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susannapaoli/network-visualization-and-style-transfer

Model visualization and style transfer

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speediedan/deep_classiflie

Deep Classiflie is a framework for developing ML models that bolster fact-checking efficiency. As a POC, the initial alpha release of Deep Classiflie generates/analyzes a model that continuously classifies a single individual's statements (Donald Trump) using a single ground truth labeling source (The Washington Post). For statements the model deems most likely to be labeled falsehoods, the @DeepClassiflie twitter bot tweets out a statement analysis and model interpretation "report"

Language: Python - Size: 204 MB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

robinvanschaik/interpret-flair

A small repository to test Captum Explainable AI with a trained Flair transformers-based text classifier.

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ProGamerGov/captum-tutorials

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nicovandenhooff/indoor-scene-detector

This repository contains the source code for Indoor Scene Detector, a full stack deep learning computer vision application.

Language: Python - Size: 170 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

LuanAdemi/VisualGo

Training a CNN to recognize the current Go position with photorealistic renders

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speediedan/deep_classiflie_db

Deep_classiflie_db is the backend data system for managing Deep Classiflie metadata, analyzing Deep Classiflie intermediate datasets and orchestrating Deep Classiflie model training pipelines. Deep_classiflie_db includes data scraping modules for the initial model data sources. Deep Classiflie depends upon deep_classiflie_db for much of its analytical and dataset generation functionality but the data system is currently maintained as a separate repository here to maximize architectural flexibility. Depending on how Deep Classiflie evolves (e.g. as it supports distributed data stores etc.), it may make more sense to integrate deep_classiflie_db back into deep_classiflie. Currently, deep_classiflie_db releases are synchronized to deep_classiflie releases. To learn more, visit deepclassiflie.org.

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yuneg11/Interpretability-Metrics

Interpretability Metrics

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