Alternatives and similar repositories for BayLime

Users that are interested in BayLime are comparing it to the libraries listed below

• ZhengzeZhou / slime
  ☆17Updated 2 years ago
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated 2 years ago
• donato-maragno / robust-CE
  Generate robust counterfactual explanations for machine learning models
  ☆16Updated 2 years ago
• dylan-slack / Fooling-LIME-SHAP
  Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
  ☆83Updated 2 years ago
• SinaMohseni / Awesome-XAI-Evaluation
  Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systems
  ☆74Updated 3 years ago
• rajesh-lab / realx
  ☆10Updated 3 years ago
• steven7woo / fair_regression_reduction
  General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.
  ☆16Updated 5 years ago
• AI4LIFE-GROUP / OpenXAI
  OpenXAI : Towards a Transparent Evaluation of Model Explanations
  ☆247Updated 11 months ago
• charmlab / mace
  Model Agnostic Counterfactual Explanations
  ☆87Updated 2 years ago
• abacusai / xai-bench
  XAI-Bench is a library for benchmarking feature attribution explainability techniques
  ☆70Updated 2 years ago
• ykwon0407 / fast_dist_shapley
  Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)
  ☆22Updated last year
• clinicalml / learn-to-defer
  Code for "Consistent Estimators for Learning to Defer to an Expert" (ICML 2020)
  ☆13Updated 2 years ago
• raj-shah / senn
  Towards Robust Interpretability with Self-Explaining Neural Networks, Alvarez-Melis et al. 2018
  ☆15Updated 5 years ago
• divyat09 / cf-feasibility
  Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"
  ☆31Updated 2 years ago
• chihkuanyeh / concept_exp
  code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"
  ☆53Updated 3 years ago
• MartinPawelczyk / c-chvae
  ☆11Updated 4 years ago
• wangyongjie-ntu / CFAI
  A collection of algorithms of counterfactual explanations.
  ☆50Updated 4 years ago
• iancovert / fastshap
  An amortized approach for calculating local Shapley value explanations
  ☆98Updated last year
• geifmany / uncertainty_ICLR
  Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019
  ☆14Updated 6 years ago
• a-lucic / focus
  ☆16Updated 3 years ago
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆35Updated last year
• iancovert / shapley-regression
  For calculating Shapley values via linear regression.
  ☆70Updated 4 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆55Updated last year
• chihkuanyeh / saliency_evaluation
  Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for…
  ☆25Updated 3 years ago
• GDPlumb / ExpO
  Explanation Optimization
  ☆13Updated 4 years ago
• laura-rieger / deep-explanation-penalization
  Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…
  ☆128Updated 4 years ago
• jmikko / fair_ERM
  Fair Empirical Risk Minimization (FERM)
  ☆37Updated 4 years ago
• samzabdiel / XAI
  Papers and code of Explainable AI esp. w.r.t. Image classificiation
  ☆214Updated 3 years ago
• JHoelli / TSEvo
  "TSEvo: Counterfactuals for Time Series Classification" accepted at ICMLA '22.
  ☆14Updated 2 years ago
• ahmedmagdiosman / clevr-xai
  Dataset and code for the CLEVR-XAI dataset.
  ☆31Updated last year