https://github.com/aix-group/ppm-survey
공식 코드This looks like what? Challenges and Future Research Directions for Part-Prototype Models
Papers with Code 아카이브
Explainable Artificial Intelligence (XAI)
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Explainable Artificial Intelligence
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/aixplain/NoRefER
공식 코드https://github.com/alonjacovi/xai-scholar
공식 코드https://github.com/amaa11/Additive-Effects-of-Collinearity
공식 코드Explainable Artificial Intelligence for Dependent Features: Additive Effects of Collinearity
https://github.com/amaa11/mip
공식 코드Characterizing the contribution of dependent features in XAI methods
https://github.com/amamalak/xai_fidelity_assessment_cnn_geo
공식 코드https://github.com/ameenali/xai_transformers
공식 코드XAI for Transformers: Better Explanations through Conservative Propagation
https://github.com/aminnayebi/xaicomparison
공식 코드https://github.com/amparore/leaf
공식 코드To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods
https://github.com/analytics-everywhere-lab/heart2mind
공식 코드https://github.com/andreartelt/diversesemifactualsreject
공식 코드https://github.com/anguyen8/nearest-neighbor-XAI
공식 코드https://github.com/annahedstroem/MetaQuantus
공식 코드The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus
https://github.com/annahedstroem/sanity-checks-revisited
공식 코드Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test
https://github.com/ant-research/BayesianLinearAttributionForRootCauseLocalization_BALANCE
공식 코드BALANCE: Bayesian Linear Attribution for Root Cause Localization
https://github.com/apple2373/wbcatt
공식 코드WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributes
https://github.com/arjunakula/faultline_explainer
공식 코드https://github.com/ayanglab/xai_covid-19
공식 코드Explainable COVID-19 Infections Identification and Delineation Using Calibrated Pseudo Labels
https://github.com/bach1292/xagent
공식 코드From Black Boxes to Conversations: Incorporating XAI in a Conversational Agent
https://github.com/basvandervelden/mmvca
공식 코드https://github.com/billyl320/wbc_luke
공식 코드https://github.com/biomed-AI/MolRep
공식 코드Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction
https://github.com/bips-hb/carfi_paper
공식 코드Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests
https://github.com/boevkoski/xaicl_parliaments
공식 코드XAI in Computational Linguistics: Understanding Political Leanings in the Slovenian Parliament
https://github.com/braindatalab/gecobench
공식 코드GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations
https://github.com/braindatalab/scrutinizing-xai
공식 코드Scrutinizing XAI using linear ground-truth data with suppressor variables
https://github.com/braindatalab/xai-tris
공식 코드https://github.com/briankeithn/narrative-maps
공식 코드https://github.com/brunompacheco/sat-gnn
공식 코드Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem
https://github.com/capitalone/ablation
공식 코드BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence
https://github.com/cebudding/medneurips_2021
공식 코드Evaluating saliency methods on artificial data with different background types
https://github.com/chilab1/hge
공식 코드Unveiling Molecular Moieties through Hierarchical Grad-CAM Graph Explainability
https://github.com/chr5tphr/zennit
공식 코드https://github.com/christophM/paper_conditional_subgroups
공식 코드Explainable Artificial Intelligence and Multicollinearity : A Mini Review of Current Approaches
https://github.com/citoverse/amesoeder-et-al-2023
공식 코드https://github.com/cohenyo/xai-clustering-phm
공식 코드Shapley-based Explainable AI for Clustering Applications in Fault Diagnosis and Prognosis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.