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Search results for python explainability
explainability
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66 search results found
Shapash
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2,547
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Neural Backed Decision Trees
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445
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
Score Cam
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310
Official implementation of Score-CAM in PyTorch
Tf Keras Vis
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286
Neural network visualization toolkit for tf.keras
Carla
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216
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
Sage
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205
For calculating global feature importance using Shapley values.
Whitebox
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184
[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes
Hatexplain
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152
Can we use explanations to improve hate speech models? Our paper accepted at AAAI 2021 tries to explore that question.
Zennit
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151
Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
Chatgpt_for_ie
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129
Evaluating ChatGPT’s Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness
Hierarchical Dnn Interpretations
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119
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Sagemaker Explaining Credit Decisions
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87
Amazon SageMaker Solution for explaining credit decisions.
Rrl
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82
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"
Pytorch_explain
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80
PyTorch Explain: Logic Explained Networks in Python.
Deep Explanation Penalization
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74
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
Talktomodel
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68
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
Fat Forensics
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63
Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
S3bert
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61
Semantically Structured Sentence Embeddings
Imodelsx
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60
Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.
Cxplain
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59
Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
Stagin
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55
STAGIN: Spatio-Temporal Attention Graph Isomorphism Network
Azimuth
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50
Helping AI practitioners better understand their datasets and models in text classification. From ServiceNow.
Vog
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49
Estimating Example Difficulty using Variance of Gradients
Prototree
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46
ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021
Bunkatopics
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43
🗺️ Data Cleaning and Textual Data Visualization 🗺️
Influenciae
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42
👋 Influenciae is a Tensorflow Toolbox for Influence Functions
Concept Based Xai
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37
Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
Carp
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36
The implementation of “A Capsule Network for Recommendation and Explaining What You Like and Dislike”, Chenliang Li, Cong Quan, Li Peng, Yunwei Qi, Yuming Deng, Libing Wu, https://dl.acm.org/citation.cfm?doid=3331184.33312
Lda4rec
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34
🧮 Extended Latent Dirichlet Allocation for Collaborative Filtering in Recommender Systems.
Cem
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26
Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off"
Te2rules
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25
Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.
Avsl
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24
[CVPR 2022] Official PyTorch implementation for Attributable Visual Similarity Learning
Removal Explanations
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24
A lightweight implementation of removal-based explanations for ML models.
Explanation Quality Recsys
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23
Post Processing Explanations Paths in Path Reasoning Recommender Systems with Knowledge Graphs
Rgcl
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23
Ratioanle-aware Graph Contrastive Learning codebase
Clevr X
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21
CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations
Tradernet Crv2
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18
TraderNet-CRv2 - Combining Deep Reinforcement Learning with Technical Analysis and Trend Monitoring on Cryptocurrency Markets
Hyphen
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17
[NeurIPS 2022 Oral (Spotlight)] Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classification
Modeling Uncertainty Local Explainability
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16
Local explanations with uncertainty 💐!
Automlx
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16
This repository contains demo notebooks (sample code) for the AutoMLx (automated machine learning and explainability) package from Oracle Labs.
Lernd
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15
Lernd is ∂ILP (dILP) framework implementation based on Deepmind's paper Learning Explanatory Rules from Noisy Data.
Ablation
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15
Evaluating XAI methods through ablation studies.
Timellama
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14
The official repo of TimeLlama, an instruction-finetuned Llama2 series that improve complex temporal reasoning ability.
Teex
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14
A Toolbox for the Evaluation of machine learning Explanations
Diffi
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14
Interpretation of Isolation Forests
Trustyai Explainability
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13
TrustyAI Explainability Toolkit
Sotai
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12
Mllp
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12
The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
Explainable Cso
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11
Code for "Explainable Data-Driven Optimization" (ICML 2023)
Pytolemaic
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10
Toolbox for analysis of model's quality and model's description. For further details see
Streamlit Shap
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10
streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
Nwhead
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9
Code for the Nadaraya-Watson Head - an interpretable/explainable, nonparametric classification head which can be used with any neural network
Protopdebug
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9
Implementation of Concept-level Debugging of Part-Prototype Networks
Micromodels
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9
Micromodels -- A framework for accurate, explainable, data efficient, and reusable NLP models.
Saliency Faithfulness Eval
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8
A suite of tests to assess attention faithfulness for explainability
Shapley Regression
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8
For calculating Shapley values via linear regression.
Model Guidance
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8
Code for the paper: Studying How to Efficiently and Effectively Guide Models with Explanations. ICCV 2023.
Explainable Models With Consistent Interpretations
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8
Official repository for the AAAI-21 paper 'Explainable Models with Consistent Interpretations'
Doxpy
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7
Replication package for the KNOSYS paper titled "An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability".
Deepinfoflow
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7
Tree_influence
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7
Influence Estimation for Gradient-Boosted Decision Trees
Timex
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6
Time series explainability via self-supervised model behavior consistency
Explainability_for_photonics
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5
Here, we use Deep SHAP (or SHAP) to explain the behavior of nanophotonic structures learned by a convolutional neural network (CNN). Reference: https://pubs.acs.org/doi/full/10.1021/acsphotonics
Xper
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5
A methodology designed to measure the contribution of the features to the predictive performance of any econometric or machine learning model.
Xwhy
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5
Explaining black boxes with a SMILE: Statistical Mode-agnostic Interpretability with Local Explanations
Functional_attribution
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5
Code of our accepted ICML 2021 paper "Towards Rigorous Interpretations: a Formalisation of Feature Attribution" (D. Afchar, R. Hennequin, V. Guigue)
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