Alternatives and similar repositories for zennit-crp:

Users that are interested in zennit-crp are comparing it to the libraries listed below

• chr5tphr / zennit
  Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
  ☆214Updated 8 months ago
• kaifishr / PyTorchRelevancePropagation
  A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.
  ☆89Updated 2 years ago
• annahedstroem / MetaQuantus
  MetaQuantus is an XAI performance tool to identify reliable evaluation metrics
  ☆34Updated 11 months ago
• maxdreyer / Reveal2Revise
  Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. Paper presented at MICCAI 2023 conference.
  ☆19Updated last year
• rachtibat / LRP-eXplains-Transformers
  Layer-Wise Relevance Propagation for Large Language Models and Vision Transformers [ICML 2024]
  ☆137Updated this week
• maxdreyer / L-CRP
  Concept Relevance Propagation for Localization Models, accepted at SAIAD workshop at CVPR 2023.
  ☆14Updated last year
• ahmedmagdiosman / clevr-xai
  Dataset and code for the CLEVR-XAI dataset.
  ☆31Updated last year
• fhvilshoj / TorchLRP
  A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).
  ☆135Updated 4 years ago
• samzabdiel / XAI
  Papers and code of Explainable AI esp. w.r.t. Image classificiation
  ☆204Updated 2 years ago
• serre-lab / Lens
  LENS Project
  ☆47Updated last year
• lkopf / cosy
  CoSy: Evaluating Textual Explanations
  ☆16Updated 2 months ago
• deel-ai / Craft
  👋 Code for : "CRAFT: Concept Recursive Activation FacTorization for Explainability" (CVPR 2023)
  ☆62Updated last year
• understandable-machine-intelligence-lab / Quantus
  Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
  ☆594Updated last month
• jvielhaben / MCD-XAI
  ☆11Updated last year
• AI4LIFE-GROUP / OpenXAI
  OpenXAI : Towards a Transparent Evaluation of Model Explanations
  ☆240Updated 7 months ago
• dilyabareeva / quanda
  A toolkit for quantitative evaluation of data attribution methods.
  ☆42Updated this week
• rodrigobdz / lrp
  Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curv…
  ☆15Updated 2 years ago
• virelay / corelay
  CoRelAy is a tool to compose small-scale (single-machine) analysis pipelines.
  ☆27Updated 2 years ago
• zhiCHEN96 / ConceptWhitening
  ☆120Updated 3 years ago
• serre-lab / Harmonization
  👋 Aligning Human & Machine Vision using explainability
  ☆51Updated last year
• pankessel / adv_explanation_ref
  reference implementation for "explanations can be manipulated and geometry is to blame"
  ☆36Updated 2 years ago
• moboehle / Pytorch-LRP
  Basic LRP implementation in PyTorch
  ☆167Updated 7 months ago
• omegafragger / DDU
  Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
  ☆135Updated last year
• mertyg / post-hoc-cbm
  Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023
  ☆74Updated 10 months ago
• AmeenAli / XAI_Transformers
  Official Code Implementation of the paper : XAI for Transformers: Better Explanations through Conservative Propagation
  ☆63Updated 3 years ago
• maxdreyer / pcx
  Prototypical Concept-based Explanations, accepted at SAIAD workshop at CVPR 2024.
  ☆13Updated last month