explainable-ai

Open-source projects categorized as explainable-ai
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Topics: Machine Learning explainable-ml Deep Learning xai Interpretability
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Top 23 explainable-ai Open-Source Projects

  • deep-learning-drizzle

    Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

  • pytorch-grad-cam

    Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

    Project mention: Exploring GradCam and More with FiftyOne | dev.to | 2024-02-13

    For the two examples we will be looking at, we will be using pytorch_grad_cam, an incredible open source package that makes working with GradCam very easy. There are excellent other tutorials to check out on the repo as well.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  • interpret

    Fit interpretable models. Explain blackbox machine learning.

  • sahi

    Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

    Project mention: Small-Object Detection using YOLOv8 | /r/computervision | 2023-08-15

    Hi All, I am trying to detect defects in the images using YOLOv8where some of the classes (defectType1, defectType2) have very small bounding boxes and some of them have large bounding boxes associated with the, (defectType3, defectType4). Also, real-time operation is desired (at least 5Hz on Jetson Xavier) What I have done till now: I am primarily trying to use the SAHI technique (Slicing Aided Hyper Inference)

  • giskard

    🐢 Open-Source Evaluation & Testing framework for LLMs and ML models

    Project mention: Show HN: Evaluate LLM-based RAG Applications with automated test set generation | news.ycombinator.com | 2024-04-11

  • awesome-explainable-graph-reasoning

    A collection of research papers and software related to explainability in graph machine learning.

  • AIX360

    Interpretability and explainability of data and machine learning models

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  • DALEX

    moDel Agnostic Language for Exploration and eXplanation

  • imodels

    Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

  • DiCE

    Generate Diverse Counterfactual Explanations for any machine learning model.

  • responsible-ai-toolbox

    Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

  • transformers-interpret

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

  • OmniXAI

    OmniXAI: A Library for eXplainable AI

  • vit-explain

    Explainability for Vision Transformers

  • Transformer-MM-Explainability

    [ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

  • awesome-open-data-centric-ai

    Curated list of open source tooling for data-centric AI on unstructured data.

  • daam

    Diffusion attentive attribution maps for interpreting Stable Diffusion.

  • xplique

    👋 Xplique is a Neural Networks Explainability Toolbox

    Project mention: Xplique Is a Neural Networks Explainability Toolbox | news.ycombinator.com | 2024-02-02

  • SymbolicRegression.jl

    Distributed High-Performance Symbolic Regression in Julia

    Project mention: Symbolicregression.jl – High-Performance Symbolic Regression in Julia and Python | news.ycombinator.com | 2023-07-15

  • FastTreeSHAP

    Fast SHAP value computation for interpreting tree-based models

  • tf-keras-vis

    Neural network visualization toolkit for tf.keras

  • inseq

    Interpretability for sequence generation models 🐛 🔍

  • CARLA

    CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms (by carla-recourse)

  • SaaSHub

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2024-04-11.

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Index

What are some of the best open-source explainable-ai projects? This list will help you:

Project Stars
1 deep-learning-drizzle 11,738
2 pytorch-grad-cam 9,351
3 interpret 5,978
4 sahi 3,534
5 giskard 3,042
6 awesome-explainable-graph-reasoning 1,934
7 AIX360 1,522
8 DALEX 1,318
9 imodels 1,284
10 DiCE 1,266
11 responsible-ai-toolbox 1,203
12 transformers-interpret 1,201
13 OmniXAI 803
14 vit-explain 708
15 Transformer-MM-Explainability 701
16 awesome-open-data-centric-ai 674
17 daam 593
18 xplique 561
19 SymbolicRegression.jl 520
20 FastTreeSHAP 492
21 tf-keras-vis 304
22 inseq 289
23 CARLA 263

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