Topic: "interpretability"
shap/shap
A game theoretic approach to explain the output of any machine learning model.
Language: Jupyter Notebook - Size: 282 MB - Last synced at: 3 days ago - Pushed at: 4 days ago - Stars: 23,949 - Forks: 3,369
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Size: 2.43 MB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 18,486 - Forks: 2,351
jacobgil/pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Language: Python - Size: 134 MB - Last synced at: 19 days ago - Pushed at: 2 months ago - Stars: 11,641 - Forks: 1,636
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
Language: C++ - Size: 14.8 MB - Last synced at: 1 day ago - Pushed at: 2 days ago - Stars: 6,516 - Forks: 749
pytorch/captum
Model interpretability and understanding for PyTorch
Language: Python - Size: 308 MB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 5,244 - Forks: 521
tensorflow/lucid 📦
A collection of infrastructure and tools for research in neural network interpretability.
Language: Jupyter Notebook - Size: 141 MB - Last synced at: 1 day ago - Pushed at: over 2 years ago - Stars: 4,691 - Forks: 653
jphall663/awesome-machine-learning-interpretability
A curated list of awesome responsible machine learning resources.
Size: 2.42 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 3,786 - Forks: 603
stellargraph/stellargraph
StellarGraph - Machine Learning on Graphs
Language: Python - Size: 92.5 MB - Last synced at: 17 days ago - Pushed at: about 1 year ago - Stars: 3,006 - Forks: 434
MAIF/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Language: Jupyter Notebook - Size: 61.8 MB - Last synced at: 18 days ago - Pushed at: 21 days ago - Stars: 2,881 - Forks: 346
SeldonIO/alibi
Algorithms for explaining machine learning models
Language: Python - Size: 30.3 MB - Last synced at: 17 days ago - Pushed at: 29 days ago - Stars: 2,502 - Forks: 257
frgfm/torch-cam
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
Language: Python - Size: 10.3 MB - Last synced at: 17 days ago - Pushed at: 22 days ago - Stars: 2,192 - Forks: 220
chaoyanghe/Awesome-Federated-Learning
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
Size: 210 KB - Last synced at: 24 days ago - Pushed at: almost 3 years ago - Stars: 1,957 - Forks: 329
google-deepmind/penzai
A JAX research toolkit for building, editing, and visualizing neural networks.
Language: Python - Size: 484 MB - Last synced at: 6 days ago - Pushed at: about 1 month ago - Stars: 1,781 - Forks: 64
ramprs/grad-cam
[ICCV 2017] Torch code for Grad-CAM
Language: Lua - Size: 1.54 MB - Last synced at: 15 days ago - Pushed at: over 2 years ago - Stars: 1,557 - Forks: 229
microsoft/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.
Language: TypeScript - Size: 111 MB - Last synced at: 1 day ago - Pushed at: 4 months ago - Stars: 1,552 - Forks: 409
wangyongjie-ntu/Awesome-explainable-AI
A collection of research materials on explainable AI/ML
Language: Markdown - Size: 1.93 MB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 1,494 - Forks: 203
stanfordnlp/pyreft
Stanford NLP Python library for Representation Finetuning (ReFT)
Language: Python - Size: 104 MB - Last synced at: 17 days ago - Pushed at: 4 months ago - Stars: 1,468 - Forks: 125
csinva/imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Language: Jupyter Notebook - Size: 162 MB - Last synced at: 6 days ago - Pushed at: 3 months ago - Stars: 1,465 - Forks: 124
ModelOriented/DALEX
moDel Agnostic Language for Exploration and eXplanation
Language: Python - Size: 798 MB - Last synced at: 17 days ago - Pushed at: 4 months ago - Stars: 1,422 - Forks: 168
cdpierse/transformers-interpret
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
Language: Jupyter Notebook - Size: 7.87 MB - Last synced at: 9 days ago - Pushed at: almost 2 years ago - Stars: 1,346 - Forks: 99
EthicalML/xai
XAI - An eXplainability toolbox for machine learning
Language: Python - Size: 17.8 MB - Last synced at: 15 days ago - Pushed at: over 3 years ago - Stars: 1,171 - Forks: 179
sicara/tf-explain
Interpretability Methods for tf.keras models with Tensorflow 2.x
Language: Python - Size: 931 KB - Last synced at: 9 days ago - Pushed at: about 1 year ago - Stars: 1,028 - Forks: 110
kundajelab/deeplift
Public facing deeplift repo
Language: Python - Size: 10.7 MB - Last synced at: 18 days ago - Pushed at: about 3 years ago - Stars: 856 - Forks: 169
shubhomoydas/ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
Language: Python - Size: 125 MB - Last synced at: 3 months ago - Pushed at: about 1 year ago - Stars: 855 - Forks: 184
hila-chefer/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.
Language: Jupyter Notebook - Size: 25.3 MB - Last synced at: 14 days ago - Pushed at: almost 2 years ago - Stars: 851 - Forks: 110
pbiecek/xai_resources
Interesting resources related to XAI (Explainable Artificial Intelligence)
Language: R - Size: 13.2 MB - Last synced at: 14 days ago - Pushed at: about 3 years ago - Stars: 830 - Forks: 138
oneTaken/awesome_deep_learning_interpretability
深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
Size: 156 KB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 747 - Forks: 122
stanfordnlp/pyvene
Stanford NLP Python library for understanding and improving PyTorch models via interventions
Language: Python - Size: 25.4 MB - Last synced at: 17 days ago - Pushed at: about 1 month ago - Stars: 742 - Forks: 82
MisaOgura/flashtorch
Visualization toolkit for neural networks in PyTorch! Demo -->
Language: HTML - Size: 68.8 MB - Last synced at: 18 days ago - Pushed at: over 1 year ago - Stars: 740 - Forks: 87
deel-ai/xplique
👋 Xplique is a Neural Networks Explainability Toolbox
Language: Python - Size: 33.4 MB - Last synced at: 9 days ago - Pushed at: 8 months ago - Stars: 689 - Forks: 58
tensorflow/decision-forests
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
Language: Python - Size: 5.94 MB - Last synced at: 1 day ago - Pushed at: 18 days ago - Stars: 680 - Forks: 113
jphall663/interpretable_machine_learning_with_python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Language: Jupyter Notebook - Size: 34.7 MB - Last synced at: 14 days ago - Pushed at: 12 months ago - Stars: 679 - Forks: 207
tensorflow/tcav
Code for the TCAV ML interpretability project
Language: Jupyter Notebook - Size: 625 KB - Last synced at: 1 day ago - Pushed at: 10 months ago - Stars: 642 - Forks: 153
alvinwan/neural-backed-decision-trees
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
Language: Python - Size: 2.57 MB - Last synced at: 14 days ago - Pushed at: about 2 years ago - Stars: 621 - Forks: 131
kmeng01/rome
Locating and editing factual associations in GPT (NeurIPS 2022)
Language: Python - Size: 22.1 MB - Last synced at: about 2 months ago - Pushed at: about 1 year ago - Stars: 620 - Forks: 138
understandable-machine-intelligence-lab/Quantus
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
Language: Jupyter Notebook - Size: 147 MB - Last synced at: 9 days ago - Pushed at: 4 months ago - Stars: 599 - Forks: 77
google/yggdrasil-decision-forests
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
Language: C++ - Size: 41.1 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 585 - Forks: 61
ndif-team/nnsight
The nnsight package enables interpreting and manipulating the internals of deep learned models.
Language: Jupyter Notebook - Size: 59.8 MB - Last synced at: about 9 hours ago - Pushed at: about 10 hours ago - Stars: 579 - Forks: 52
ScalaConsultants/Aspect-Based-Sentiment-Analysis
💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)
Language: Python - Size: 1.8 MB - Last synced at: 9 days ago - Pushed at: about 1 month ago - Stars: 570 - Forks: 90
mmschlk/shapiq
Shapley Interactions and Shapley Values for Machine Learning
Language: Python - Size: 309 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 554 - Forks: 35
linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
Language: Python - Size: 152 MB - Last synced at: 10 days ago - Pushed at: almost 2 years ago - Stars: 540 - Forks: 34
BCG-X-Official/facet
Human-explainable AI.
Language: Jupyter Notebook - Size: 50.5 MB - Last synced at: 15 days ago - Pushed at: over 1 year ago - Stars: 521 - Forks: 47
h2oai/mli-resources
H2O.ai Machine Learning Interpretability Resources
Language: Jupyter Notebook - Size: 65.8 MB - Last synced at: 12 days ago - Pushed at: over 4 years ago - Stars: 488 - Forks: 130
explainX/explainx
Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]
Language: Jupyter Notebook - Size: 61.3 MB - Last synced at: 14 days ago - Pushed at: 10 months ago - Stars: 436 - Forks: 56
inseq-team/inseq
Interpretability for sequence generation models 🐛 🔍
Language: Python - Size: 7.64 MB - Last synced at: 10 days ago - Pushed at: about 1 month ago - Stars: 419 - Forks: 38
xmed-lab/CLIP_Surgery
CLIP Surgery for Better Explainability with Enhancement in Open-Vocabulary Tasks
Language: Jupyter Notebook - Size: 18.9 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 397 - Forks: 25
pratyushasharma/laser
The Truth Is In There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Language: Python - Size: 2.25 MB - Last synced at: 5 days ago - Pushed at: 11 months ago - Stars: 386 - Forks: 34
IAAR-Shanghai/Awesome-Attention-Heads
An awesome repository & A comprehensive survey on interpretability of LLM attention heads.
Language: TeX - Size: 6.07 MB - Last synced at: 28 days ago - Pushed at: 3 months ago - Stars: 348 - Forks: 12
sergioburdisso/pyss3
A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)
Language: Python - Size: 102 MB - Last synced at: about 9 hours ago - Pushed at: about 10 hours ago - Stars: 341 - Forks: 44
ModelOriented/modelStudio
📍 Interactive Studio for Explanatory Model Analysis
Language: R - Size: 36.2 MB - Last synced at: 2 days ago - Pushed at: almost 2 years ago - Stars: 332 - Forks: 32
datamllab/awesome-fairness-in-ai
A curated list of awesome Fairness in AI resources
Size: 33.2 KB - Last synced at: 1 day ago - Pushed at: over 1 year ago - Stars: 321 - Forks: 66
hbaniecki/adversarial-explainable-ai
💡 Adversarial attacks on explanations and how to defend them
Size: 2.62 MB - Last synced at: 2 months ago - Pushed at: 6 months ago - Stars: 314 - Forks: 48
JoaoLages/diffusers-interpret
Diffusers-Interpret 🤗🧨🕵️♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.
Language: Jupyter Notebook - Size: 77.5 MB - Last synced at: 3 days ago - Pushed at: over 2 years ago - Stars: 277 - Forks: 14
iancovert/sage
For calculating global feature importance using Shapley values.
Language: Python - Size: 7.93 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 270 - Forks: 35
SteveKGYang/MentalLLaMA
This repository introduces MentaLLaMA, the first open-source instruction following large language model for interpretable mental health analysis.
Language: Python - Size: 13.2 MB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 264 - Forks: 27
AI4LIFE-GROUP/OpenXAI
OpenXAI : Towards a Transparent Evaluation of Model Explanations
Language: JavaScript - Size: 41.7 MB - Last synced at: about 1 month ago - Pushed at: 10 months ago - Stars: 245 - Forks: 43
haofanwang/Awesome-Computer-Vision
Awesome Resources for Advanced Computer Vision Topics
Size: 93.8 KB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 230 - Forks: 43
hijohnnylin/neuronpedia
open source interpretability platform 🧠
Language: TypeScript - Size: 13.1 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 227 - Forks: 28
chr5tphr/zennit
Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
Language: Python - Size: 2.28 MB - Last synced at: 13 days ago - Pushed at: 11 months ago - Stars: 226 - Forks: 34
g8a9/ferret
A python package for benchmarking interpretability techniques on Transformers.
Language: Python - Size: 1.52 MB - Last synced at: 24 days ago - Pushed at: 8 months ago - Stars: 211 - Forks: 15
ArrasL/LRP_for_LSTM
Layer-wise Relevance Propagation (LRP) for LSTMs.
Language: Python - Size: 12.4 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 204 - Forks: 58
rigvedrs/YOLO-V11-CAM
Wanna know what your model sees? Here's a package for applying EigenCAM and generating heatmap from the new YOLO V11 model
Language: Jupyter Notebook - Size: 40 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 201 - Forks: 42
ShengcaiLiao/QAConv
[ECCV 2020] QAConv: Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting, and [CVPR 2022] GS: Graph Sampling Based Deep Metric Learning
Language: Python - Size: 5.42 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 188 - Forks: 30
pralab/secml
A Python library for Secure and Explainable Machine Learning
Language: Jupyter Notebook - Size: 67.2 MB - Last synced at: 14 days ago - Pushed at: 4 months ago - Stars: 176 - Forks: 26
PKU-Alignment/aligner
[NeurIPS 2024 Oral] Aligner: Efficient Alignment by Learning to Correct
Language: Python - Size: 16.3 MB - Last synced at: 13 days ago - Pushed at: 5 months ago - Stars: 175 - Forks: 9
jrieke/cnn-interpretability
🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease
Language: Jupyter Notebook - Size: 61.5 MB - Last synced at: 3 days ago - Pushed at: almost 6 years ago - Stars: 171 - Forks: 50
Graph-COM/GSAT
[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
Language: Jupyter Notebook - Size: 1.57 MB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 167 - Forks: 22
mims-harvard/GraphXAI
GraphXAI: Resource to support the development and evaluation of GNN explainers
Language: Python - Size: 249 MB - Last synced at: 7 months ago - Pushed at: about 1 year ago - Stars: 166 - Forks: 29
csinva/imodelsX
Interpret text data using LLMs (scikit-learn compatible).
Language: Python - Size: 35 MB - Last synced at: 15 days ago - Pushed at: 3 months ago - Stars: 165 - Forks: 26
AustinRochford/PyCEbox
⬛ Python Individual Conditional Expectation Plot Toolbox
Language: Jupyter Notebook - Size: 1.15 MB - Last synced at: 28 days ago - Pushed at: about 5 years ago - Stars: 165 - Forks: 35
poloclub/timbertrek
Explore and compare 1K+ accurate decision trees in your browser!
Language: TypeScript - Size: 36.9 MB - Last synced at: 29 days ago - Pushed at: over 1 year ago - Stars: 161 - Forks: 10
EleutherAI/knowledge-neurons
A library for finding knowledge neurons in pretrained transformer models.
Language: Python - Size: 11.6 MB - Last synced at: 29 days ago - Pushed at: over 3 years ago - Stars: 157 - Forks: 18
pietrobarbiero/pytorch_explain
PyTorch Explain: Interpretable Deep Learning in Python.
Language: Jupyter Notebook - Size: 42.1 MB - Last synced at: 19 days ago - Pushed at: about 1 year ago - Stars: 154 - Forks: 14
google-research/reverse-engineering-neural-networks
A collection of tools for reverse engineering neural networks.
Language: Jupyter Notebook - Size: 2.79 MB - Last synced at: 18 days ago - Pushed at: over 1 year ago - Stars: 153 - Forks: 28
vanderschaarlab/autoprognosis
A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
Language: Python - Size: 960 KB - Last synced at: 25 days ago - Pushed at: 2 months ago - Stars: 147 - Forks: 28
DFKI-NLP/thermostat
Collection of NLP model explanations and accompanying analysis tools
Language: Jsonnet - Size: 1.37 MB - Last synced at: 17 days ago - Pushed at: almost 2 years ago - Stars: 145 - Forks: 8
yulongwang12/visual-attribution
Pytorch Implementation of recent visual attribution methods for model interpretability
Language: Jupyter Notebook - Size: 27.7 MB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 141 - Forks: 25
mahmoodlab/SurvPath
Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction - CVPR 2024
Language: Python - Size: 99.6 MB - Last synced at: 13 days ago - Pushed at: 7 months ago - Stars: 137 - Forks: 11
JHoelli/Awesome-Time-Series-Explainability
A list of (post-hoc) XAI for time series
Size: 424 KB - Last synced at: 24 days ago - Pushed at: 9 months ago - Stars: 135 - Forks: 16
jasonjmcghee/livelove
Love2D LSP (VS Code / Neovim / Zed / etc.) extension for live coding and live variable tracking
Language: JavaScript - Size: 5.33 MB - Last synced at: 19 days ago - Pushed at: about 1 month ago - Stars: 134 - Forks: 2
fzi-forschungszentrum-informatik/TSInterpret
An Open-Source Library for the interpretability of time series classifiers
Language: Python - Size: 200 MB - Last synced at: 6 days ago - Pushed at: 6 months ago - Stars: 134 - Forks: 15
JunjH/Visualizing-CNNs-for-monocular-depth-estimation
official implementation of "Visualization of Convolutional Neural Networks for Monocular Depth Estimation"
Language: Python - Size: 1.38 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 134 - Forks: 28
PKU-Alignment/AlignmentSurvey
AI Alignment: A Comprehensive Survey
Size: 4.04 MB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 133 - Forks: 1
yewsiang/ConceptBottleneck
Concept Bottleneck Models, ICML 2020
Language: Python - Size: 1.51 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 132 - Forks: 23
csinva/hierarchical-dnn-interpretations
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Language: Jupyter Notebook - Size: 48.7 MB - Last synced at: 25 days ago - Pushed at: almost 4 years ago - Stars: 128 - Forks: 23
laura-rieger/deep-explanation-penalization
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
Language: Jupyter Notebook - Size: 248 MB - Last synced at: 29 days ago - Pushed at: about 4 years ago - Stars: 127 - Forks: 14
zxhuang1698/interpretability-by-parts
Code repository for "Interpretable and Accurate Fine-grained Recognition via Region Grouping", CVPR 2020 (Oral)
Language: Python - Size: 11.2 MB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 127 - Forks: 27
interpretml/gam-changer
Editing machine learning models to reflect human knowledge and values
Language: JavaScript - Size: 18.7 MB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 124 - Forks: 11
ThyrixYang/awesome-artificial-intelligence-research
A curated list of Artificial Intelligence (AI) Research, tracks the cutting edge trending of AI research, including recommender systems, computer vision, machine learning, etc.
Size: 44.9 KB - Last synced at: 28 days ago - Pushed at: over 2 years ago - Stars: 124 - Forks: 14
dylan-slack/TalkToModel
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
Language: Python - Size: 10.1 MB - Last synced at: about 2 months ago - Pushed at: almost 2 years ago - Stars: 120 - Forks: 25
KennethEnevoldsen/asent
Asent is a python library for performing efficient and transparent sentiment analysis using spaCy.
Language: Python - Size: 54.2 MB - Last synced at: 12 days ago - Pushed at: about 1 year ago - Stars: 118 - Forks: 16
d909b/cxplain
Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
Language: Python - Size: 262 KB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 118 - Forks: 34
OpenMOSS/Language-Model-SAEs
For OpenMOSS Mechanistic Interpretability Team's Sparse Autoencoder (SAE) research.
Language: Python - Size: 10.1 MB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 115 - Forks: 13
fredhohman/summit
🏔️ Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Language: JavaScript - Size: 14.4 MB - Last synced at: 6 days ago - Pushed at: over 5 years ago - Stars: 115 - Forks: 15
Julia-XAI/ExplainableAI.jl
Explainable AI in Julia.
Language: Julia - Size: 41.6 MB - Last synced at: 13 days ago - Pushed at: about 2 months ago - Stars: 112 - Forks: 3
chi0tzp/WarpedGANSpace
[ICCV 2021] Authors official PyTorch implementation of the "WarpedGANSpace: Finding non-linear RBF paths in GAN latent space".
Language: Python - Size: 439 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 110 - Forks: 6
andreysharapov/xaience
All about explainable AI, algorithmic fairness and more
Language: HTML - Size: 7.81 GB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 106 - Forks: 12
pbiecek/breakDown
Model Agnostics breakDown plots
Language: R - Size: 20.2 MB - Last synced at: 18 days ago - Pushed at: about 1 year ago - Stars: 103 - Forks: 16
M-Nauta/ProtoTree
ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021
Language: Python - Size: 870 KB - Last synced at: 29 days ago - Pushed at: almost 3 years ago - Stars: 101 - Forks: 21
whyisyoung/CADE
Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications
Language: Python - Size: 188 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 99 - Forks: 31
