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Interpretable Machine Learning

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하위 태스크: 2
평가표: 1
보존된 평가 기록: 2

The goal of Interpretable Machine Learning is to allow oversight and understanding of machine-learned decisions. Much of the work in Interpretable Machine Learning has come in the form of devising methods to better explain the predictions of machine learning models.

Source: Assessing the Local Interpretability of Machine Learning Models

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/vidalt/OCEAN

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Optimal Counterfactual Explanations in Tree Ensembles

https://github.com/visual-xai-for-time-series/time-series-xai-perturbation-analysis

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A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI

https://github.com/vojtech-balek/llm-features

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LLM-based feature generation from text for interpretable machine learning

https://github.com/vrcmf/dmon

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DMON: A Simple yet Effective Approach for Argument Structure Learning

https://github.com/wangtongada/HyRS

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Gaining Free or Low-Cost Transparency with Interpretable Partial Substitute

https://github.com/warisgill/tracefl

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TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance

https://github.com/warnikchow/sae4k

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Extracting Arguments from Korean Question and Command: An Annotated Corpus for Structured Paraphrasing

https://github.com/wdiepeveen/iso-Riemannian-geometry

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Manifold Learning with Normalizing Flows: Towards Regularity, Expressivity and Iso-Riemannian Geometry

https://github.com/webis-de/argmining-21

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Key Point Analysis via Contrastive Learning and Extractive Argument Summarization

https://github.com/webis-de/naacl-24

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A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality

https://github.com/webis-de/ratio-24

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Are Large Language Models Reliable Argument Quality Annotators?

https://github.com/willieneis/bayesian-algorithm-execution

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Improving Accuracy of Interpretability Measures in Hyperparameter Optimization via Bayesian Algorithm Execution

https://github.com/woshixuhao/worth_of_knowledge

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Worth of knowledge in deep learning

https://github.com/wuhanstudio/interpretable-ml-covid-19

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Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task

https://github.com/wumin86/prunesymnet

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PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression

https://github.com/wwoods/adversarial-explanations-cifar

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Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness

https://github.com/yanzhuguo/substanreview

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Automatic Analysis of Substantiation in Scientific Peer Reviews

https://github.com/ydup/Anomaly-Detection-in-Time-Series-with-Triadic-Motif-Fields

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Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification

https://github.com/ydup/bokeh

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Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification

https://github.com/yevzh/llm4cd-release

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LLM4CD: Leveraging Large Language Models for Open-World Knowledge Augmented Cognitive Diagnosis

https://github.com/yiqiao-yin/YinsRLab

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An Interaction-based Convolutional Neural Network (ICNN) Towards Better Understanding of COVID-19 X-ray Images

https://github.com/yohanjo/emnlp20_prop_extr

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Extracting Implicitly Asserted Propositions in Argumentation

https://github.com/yohanjo/tacl_arg_rel

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Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes

https://github.com/yuanhaoguo/circular-camera-calibration

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Probabilistic Inference for Camera Calibration in Light Microscopy under Circular Motion

https://github.com/yuanluo/panther

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PANTHER: Pathway Augmented Nonnegative Tensor factorization for HighER-order feature learning

https://github.com/yunzhe-zhou/GenericDistillation

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A Generic Approach for Reproducible Model Distillation

https://github.com/zehui127/1d-swin

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Genomic Interpreter: A Hierarchical Genomic Deep Neural Network with 1D Shifted Window Transformer

https://github.com/zekaouinoureddine/Opinion-Transformers

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Analysis of the Evolution of Advanced Transformer-Based Language Models: Experiments on Opinion Mining

https://github.com/zekavat-itrc/sentiment-analysis

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Constructing Colloquial Dataset for Persian Sentiment Analysis of Social Microblogs

https://github.com/zeroix15/Twitter_Sarcasm_Detections

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Sarcasm Detection in Twitter -- Performance Impact while using Data Augmentation: Word Embeddings

https://github.com/zhangaipi/dim

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Discover and Mitigate Multiple Biased Subgroups in Image Classifiers

https://github.com/zhichen96/interpretable_ml_metamaterials

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How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning

https://github.com/zychowskia/icoevordf

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Cultivating Archipelago of Forests: Evolving Robust Decision Trees through Island Coevolution

https://github.com/zzdyyy/Patho-GAN

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Explainable Diabetic Retinopathy Detection and Retinal Image Generation

https://github.com/zzhuyii/generateorigamidataset

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Harnessing Interpretable Machine Learning for Holistic Inverse Design of Origami

https://github.com/zzhuyii/treefororigami

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Harnessing Interpretable Machine Learning for Holistic Inverse Design of Origami

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