awesome-xai
Papers about Explainable AI (Deep Learning-based)
https://github.com/fawazsammani/awesome-xai
Last synced: 17 days ago
JSON representation
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Papers
- [pdf - chefer/Transformer-MM-Explainability)
- [pdf - vs-shape)
- MACO - lab.github.io/Lens/)
- [pdf - axiomatic-attribution)
- [pdf - chefer/Conceptor) [[website]](https://hila-chefer.github.io/Conceptor/)
- [blog
- [pdf - things-vits/code-samples/blob/main/probing/mean_attention_distance.ipynb)
- [pdf - menon/classify_by_description_release) [[website]](https://cv.cs.columbia.edu/sachit/classviadescr/)
- [pdf - engineering) [[website]](https://www.ai-transparency.org/)
- [pdf - interpretability.csail.mit.edu/Multimodal-Neurons-in-Text-Only-Transformers/)
- AMC
- XIL
- CDEP
- MaskTune
- ClickMe
- CoDA-Nets
- ABN
- RES
- IAA
- DiFull - Evaluation)
- AttentionViz
- Rosetta Neurons
- SAFARI
- LANCE - web/)
- FunnyBirds
- MAGI
- CCE
- [pdf - lab/Meta-predictor) [[blog]](https://serre-lab.github.io/Meta-predictor/)
- [pdf - saliency-maps)
- [pdf - explain-black-box) [[code]](https://github.com/ruthcfong/pytorch-explain-black-box) [[code]](https://github.com/da2so/Interpretable-Explanations-of-Black-Boxes-by-Meaningful-Perturbation)
- [pdf - pytorch) [[code]](https://pytorch.org/tutorials/beginner/fgsm_tutorial.html)
- [pdf - CS/ConvergeSmooth)
- [pdf - Explanations) [[slides]](https://gukyeongkwon.github.io/slides/mohit_icip2020_slides.pdf)
- [pdf - chefer/Transformer-Explainability) [[video]](https://www.youtube.com/watch?v=a0O_QhE9XFM&ab_channel=DataScienceBond)
- [pdf - chefer/Transformer-MM-Explainability)
- [pdf - chefer/RobustViT)
- [pdf - eXplain-AI/Do-Explanations-Explain)
- [pdf - PredDiff)
- [pdf - vs-shape)
- [pdf - attribution-methods)
- [pdf - postech/gradient-inversion-generative-image-prior)
- [pdf - attribution-evaluation)
- [pdf - thomas/Sobol-Attribution-Method)
- [pdf - Models-with-Consistent-Interpretations)
- [pdf - GZM&t=1034s&ab_channel=VipulVaibhaw)
- [pdf - eXplain-AI/PathwayGrad) [[code]](https://github.com/CAMP-eXplain-AI/RoarTorch)
- [pdf - Visualization)
- [pdf - Naseer/Intriguing-Properties-of-Vision-Transformers)
- [pdf - invariance) [[project]](https://jakehlee.github.io/visualize-invariance)
- [pdf - Explainability)
- [pdf - visualization)
- [pdf - Zilence/Explain_Metric_Learning)
- [blog
- [pdf - trends-2020) [[code]](https://github.com/CalculatedContent/WeightWatcher) [[pip]](https://pypi.org/project/weightwatcher/) [[powerlaw]](https://github.com/jeffalstott/powerlaw)
- [blog - explain)
- [pdf - vs-CNNs)
- OpenXAI - GROUP/OpenXAI) [[website]](https://open-xai.github.io/)
- TracIn
- VoG
- D-RISE
- SmoothGrad
- Integrated Gradients - the-integrated-gradients-method-works/)
- BlurIG - code/saliency)
- IDGI
- GIG - code/saliency)
- SPI
- IIA - iccv23/iia)
- Integrated Hessians
- Archipelago
- I-GOS
- MoreauGrad
- SAGs
- LRP - berlin.de/gmontavon/lrp-tutorial) [[code]](https://github.com/fhvilshoj/TorchLRP) [[code]](https://github.com/deepfindr/xai-series/blob/master/05_lrp.py) [[blog]](https://towardsdatascience.com/indepth-layer-wise-relevance-propagation-340f95deb1ea)
- RISE - people.bu.edu/vpetsiuk/rise/)
- DeepLIFT
- ROAD
- Layer Masking - 98/layer_masking)
- Summit
- SHAP
- MM-SHAP - NLP/MM-SHAP) [[video]](https://www.youtube.com/watch?v=RLaiomLMK9I&ab_channel=AICoffeeBreakwithLetitia)
- Anchors
- Layer Conductance
- BiLRP
- CGC
- DeepInversion
- GradInversion
- GradViT
- Plug-In Inversion
- GIFD
- X-OIA
- CAT-XPLAIN - XPLAIN)
- CLRP - LRP)
- HINT
- BagNet - of-local-features-models) [[blog]](https://sh-tsang.medium.com/review-bagnet-approximating-cnns-with-bag-of-local-features-models-works-surprisingly-well-on-125f4295c433)
- SMERF
- ELUDE
- C3LT
- B-cos - cos)
- ShapNets - lab/ShapleyExplanationNetworks)
- CALM - ai/calm)
- SGLRP
- DTD - Taylor-Decomposition)
- GradCAT
- FastSHAP
- VisualBackProp
- NBDT - backed-decision-trees)
- XRAI
- MeGe, ReCo
- FCDD
- DiCE - us/research/blog/open-source-library-provides-explanation-for-machine-learning-through-diverse-counterfactuals/)
- ARM - research/anti-aliasing-transformer)
- RelEx - VL/RelEx)
- X-Pruner
- ShearletX
- EVA - ai/formal-explainability)
- Guided Zoom - Zoom)
- DAAM - Attentive-Attribution-Maps)
- Diffusion Explainer - explainer/) [[video]](https://www.youtube.com/watch?v=Zg4gxdIWDds&ab_channel=PoloClubofDataScience)
- ECLIP
- CNC
- VLSlice - YWZmp3mQ3IDJuhi/view) [[video]](https://drive.google.com/file/d/1mOuvjphNb2xNDC7shoGbPwyjbfArwud4/view) [[video]](https://www.youtube.com/watch?v=2CMDcGGsMjo&list=PLUxOP3kBxs2JYA5KT0YEmNJEyjqAqLOf3&index=2&ab_channel=CollegeofEngineering-OregonStateUniversity)
- [pdf - menon/classify_by_description_release) [[website]](https://cv.cs.columbia.edu/sachit/classviadescr/)
- [pdf - postech/gradient-inversion-generative-image-prior)
- DiCE - us/research/blog/open-source-library-provides-explanation-for-machine-learning-through-diverse-counterfactuals/)
- MoreauGrad
- GIFD
- ClickMe
- X-OIA
- [pdf - image-prior) [[code]](https://github.com/safwankdb/Deep-Image-Prior) [[code]](https://mlpeschl.com/post/deepimageprior/) [[website]](https://dmitryulyanov.github.io/deep_image_prior)
- [pdf - image-prior) [[code]](https://github.com/safwankdb/Deep-Image-Prior) [[code]](https://mlpeschl.com/post/deepimageprior/) [[website]](https://dmitryulyanov.github.io/deep_image_prior)
- [pdf - saliency-maps)
- Layer Conductance
- XRAI
- SGLRP
- [pdf - eXplain-AI/Do-Explanations-Explain)
- [pdf - trends-2020) [[code]](https://github.com/CalculatedContent/WeightWatcher) [[pip]](https://pypi.org/project/weightwatcher/) [[powerlaw]](https://github.com/jeffalstott/powerlaw)
- Summit
- Guided Zoom - Zoom)
- MACO - lab.github.io/Lens/)
- CNN Filter DB - Filter-DB)
- Feature Sieve - on-early-readouts-for.html)
- DeepInversion
- [pdf - Naseer/Intriguing-Properties-of-Vision-Transformers)
- TracIn
- FCDD
- HINT
- ShearletX
- [pdf - explain-black-box) [[code]](https://github.com/ruthcfong/pytorch-explain-black-box) [[code]](https://github.com/da2so/Interpretable-Explanations-of-Black-Boxes-by-Meaningful-Perturbation)
- [pdf - CS/ConvergeSmooth)
- [pdf - attribution-evaluation)
- OpenXAI - GROUP/OpenXAI) [[website]](https://open-xai.github.io/)
- [pdf - thomas/Sobol-Attribution-Method)
- SHAP
- CLRP - LRP)
- B-cos - cos)
- NBDT - backed-decision-trees)
- MeGe, ReCo
- CNC
- [pdf - chefer/RobustViT)
- [pdf - PredDiff)
- [pdf - Explanations) [[slides]](https://gukyeongkwon.github.io/slides/mohit_icip2020_slides.pdf)
- [pdf - chefer/Transformer-Explainability) [[video]](https://www.youtube.com/watch?v=a0O_QhE9XFM&ab_channel=DataScienceBond)
-
Other Resources
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- OpenAI Microscope
- Summary - Captum
- Alibi Docs
- jacobgil blogs
- Stanford CS231n slides
- TU Berlin Notes
- [Early Methods - NOCIITM) [[CAM Methods]](https://www.youtube.com/watch?v=VmbBnSv3otc&ab_channel=NPTEL-NOCIITM) [[Recent Methods]](https://www.youtube.com/watch?v=9OzwN-Ub6Lg&ab_channel=NPTEL-NOCIITM) [[Beyond Explaining]](https://www.youtube.com/watch?v=9Moxmab_Y4I&ab_channel=NPTEL-NOCIITM)
- AI Explained Video Series by Fiddler AI
- XAI Explained Video Series by DeepFindr
- Visualizing and Understanding Stanford Video
- CVPR 2021 Tutorial
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- [tutorial - one-pytorch-trick-which-you-should-know-2d5e9c1da2ca) [[tutorial]](https://medium.com/the-dl/how-to-use-pytorch-hooks-5041d777f904) [[tutorial]](https://pytorch.org/tutorials/beginner/former_torchies/nnft_tutorial.html)
- [tutorial
- Transformer Circuits
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- [tutorial
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- [blog - feature-maps-visualizer-snake-version/notebook) [[blog]](https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/) [[pytorch discuss]](https://discuss.pytorch.org/t/visualize-feature-map/29597/2)
-
Neuron Annotation
- Network Dissection
- LaViSE
- MILAN - descriptions) [[website]](http://milan.csail.mit.edu/)
- DeViL
- FALCON - explain)
- ZS-A2T - A2T)
- Net2Vec
- CLIP-Dissect - ML-Lab/CLIP-dissect)
- INViTE - interpret)
- CLIP-Decomposition
- STAIR
- DISCOVER
-
XAI for NLP
- [pdf - models)
- [pdf - decao/diffmask)
- [pdf - voita/the-story-of-heads)
- [pdf - benchmark)
- [pdf - you-find-these-shortcuts.html)
- [pdf - lm)
- [pdf - USC/DIG)
- [pdf - USC/hierarchical-explanation-neural-sequence-models)
- [blog
- [pdf - activations) [[website]](https://eric-mingjie.github.io/massive-activations/index.html)
-
Prototype/Concept-Based
- VRX
- SACV - Activation-Concept-Vector)
- CRP - crp)
- CRAFT - ai/Craft) [[website]](https://serre-lab.github.io/Lens/)
- ProtoTrees - Nauta/ProtoTree)
- ProtoPNet - duke/ProtoPNet)
- ST-ProtoPNet
- Deformable ProtoPNet
- SPARROW
- [pdf - vit-features.github.io/sm/index.html) [[code]](https://github.com/ShirAmir/dino-vit-features) [[website]](https://dino-vit-features.github.io/index.html)
- HINT
- ConceptSHAP
- CW
- DFF - grad-cam/blob/master/pytorch_grad_cam/feature_factorization/deep_feature_factorization.py) [[blog and code]](https://jacobgil.github.io/pytorch-gradcam-book/Deep%20Feature%20Factorizations.html)
- Proto2Proto
- PDiscoNet
- ProtoPool
- ProtoPShare
- PW-Net
- ProtoPDebug
- DSX
- ProtoSim
- FeatUp
- TCAV - ml-book/detecting-concepts.html)
- ACE
- MOCE
- ConceptExplainer
- LENS - lab.github.io/Lens/)
- SACV - Activation-Concept-Vector)
- ACE
- CRP - crp)
-
Object-Centric Learning
- SCOUTER
- SLOT-Attention - attention) [[code]](https://github.com/evelinehong/slot-attention-pytorch)
- SPOT
-
CAM Papers
- CAM
- Grad-CAM - cam/) [[code]](https://github.com/ruthcfong/pytorch-grad-cam) [[website]](http://gradcam.cloudcv.org/)
- Grad-CAM++
- Score-CAM - CAM) [[code]](https://github.com/yiskw713/ScoreCAM)
- LayerCAM - jittor)
- Eigen-CAM
- XGrad-CAM - CAM)
- Ablation-CAM
- Group-CAM - CAM)
- FullGrad
- Relevance-CAM - CAM)
- Poly-CAM
- Smooth Grad-CAM++
- Zoom-CAM
- FD-CAM - CAM)
- LIFT-CAM
- Shap-CAM
- HiResCAM
- FAM
- MinMaxCAM
-
LIME-based
-
Concept Bottleneck Models
-
Distill Papers
-
XAI/Analysis of Self-Supervised Models and Transfer Learning
- [pdf - transfer)
- [pdf - probes) [[video]](https://www.youtube.com/watch?v=l5he9JNJqHA&t=24s&ab_channel=YannicKilcher)
- [pdf - analysis) [[website]](https://mgwillia.github.io/exploring-unsupervised/)
- [pdf - InfoTech/visual-probes)
- [pdf - trained_Models_Are_from_Neural_Collapse_on_the_ICCV_2023_supplemental.pdf)
- [pdf - research/simclr/tree/master/colabs/intriguing_properties)
- [pdf - mmlab/mmpretrain)
-
Natural Language Explanations (Supervised)
- GVE
- PJ-X - Park/MultimodalExplanations)
- FME
- RVT - reasoning-rationalization)
- e-UG - ViL)
- NLX-GPT
- Uni-NLX - nlx)
- Explain Yourself
- e-SNLI
- CLEVR-X - X) [[website]](https://explainableml.github.io/CLEVR-X/)
- VQA-E
- PtE
- WT5
- RExC
- ELV
- FEB
- CALeC
- OFA-X - x/OFA-X)
- S3C
- ReVisE - lost/ReVisE)
- [pdf - deep-driving)
- Multimodal-CoT - science/mm-cot)
- CCoT
- Explain Yourself
- e-SNLI
- Multimodal-CoT - science/mm-cot)
-
Review Papers
-
XAI Libraries for Vision
-
Other Awesomes
-
Circuits/Mechanistic Interpretability
Categories
Papers
380
Other Resources
88
Prototype/Concept-Based
32
Natural Language Explanations (Supervised)
30
XAI/Analysis of Self-Supervised Models and Transfer Learning
28
XAI for NLP
26
CAM Papers
20
Neuron Annotation
12
Distill Papers
10
Concept Bottleneck Models
10
Review Papers
7
LIME-based
5
Circuits/Mechanistic Interpretability
5
Object-Centric Learning
3
XAI Libraries for Vision
2
Other Awesomes
1
Sub Categories