Imagen de Portada

Performance is not enough: the story told by a Rashomon quartet

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Biecek, Przemyslaw, Baniecki, Hubert, Krzyzinski, Mateusz, Cook, Dianne
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning Applications
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Analyzing the Temporal Factors for Anxiety and Depression Symptoms with the Rashomon Perspective
por: Cavus, Mustafa, et al.
Publicado: (2026)

Exploration of the Rashomon Set Assists Trustworthy Explanations for Medical Data
por: Kobylińska, Katarzyna, et al.
Publicado: (2023)

Birds look like cars: Adversarial analysis of intrinsically interpretable deep learning
por: Baniecki, Hubert, et al.
Publicado: (2025)

Interpretable Machine Learning for Survival Analysis
por: Langbein, Sophie Hanna, et al.
Publicado: (2024)

Adversarial attacks and defenses in explainable artificial intelligence: A survey
por: Baniecki, Hubert, et al.
Publicado: (2023)

survex: an R package for explaining machine learning survival models
por: Spytek, Mikołaj, et al.
Publicado: (2023)

Attributions All the Way Down? The Metagame of Interpretability
por: Baniecki, Hubert, et al.
Publicado: (2026)

Interpretable machine learning for time-to-event prediction in medicine and healthcare
por: Baniecki, Hubert, et al.
Publicado: (2023)

The Grammar of Interactive Explanatory Model Analysis
por: Baniecki, Hubert, et al.
Publicado: (2020)

Interpreting CLIP with Hierarchical Sparse Autoencoders
por: Zaigrajew, Vladimir, et al.
Publicado: (2025)

On the Robustness of Global Feature Effect Explanations
por: Baniecki, Hubert, et al.
Publicado: (2024)

Efficient and Accurate Explanation Estimation with Distribution Compression
por: Baniecki, Hubert, et al.
Publicado: (2024)

An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced Classification
por: Cavus, Mustafa, et al.
Publicado: (2024)

Exploring Local Explanations of Nonlinear Models Using Animated Linear Projections
por: Spyrison, Nicholas, et al.
Publicado: (2022)

A Clustering Algorithm to Organize Satellite Hotspot Data for the Purpose of Tracking Bushfires Remotely
por: Li, Weihao, et al.
Publicado: (2023)

SwordBench: Evaluating Orthogonality of Steering Image Representations
por: Zaigrajew, Vladimir, et al.
Publicado: (2026)

Rashomon perspective for measuring uncertainty in the survival predictive maintenance models
por: Yardimci, Yigitcan, et al.
Publicado: (2025)

Red-Teaming Segment Anything Model
por: Jankowski, Krzysztof, et al.
Publicado: (2024)

Beyond the Single-Best Model: Rashomon Partial Dependence Profile for Trustworthy Explanations in AutoML
por: Cavus, Mustafa, et al.
Publicado: (2025)

Interpretable Machine Learning for Survival Analysis
por: Sophie Hanna Langbein, et al.
Publicado: (2025)

Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions
por: Baniecki, Hubert, et al.
Publicado: (2025)

Investigating the Impact of Balancing, Filtering, and Complexity on Predictive Multiplicity: A Data-Centric Perspective
por: Cavus, Mustafa, et al.
Publicado: (2024)

Statistical Uncertainty Quantification for Aggregate Performance Metrics in Machine Learning Benchmarks
por: Longjohn, Rachel, et al.
Publicado: (2025)

An Analytical Approach to Privacy and Performance Trade-Offs in Healthcare Data Sharing
por: Wei, Yusi, et al.
Publicado: (2025)

Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting
por: Ghasemloo, Mohammadmahdi, et al.
Publicado: (2025)

A Comprehensive Case Study on the Performance of Machine Learning Methods on the Classification of Solar Panel Electroluminescence Images
por: Song, Xinyi, et al.
Publicado: (2024)

Feature Impact Analysis on Top Long-Jump Performances with Quantile Random Forest and Explainable AI Techniques
por: Gan, Qi, et al.
Publicado: (2025)

Player Pressure Map -- A Novel Representation of Pressure in Soccer for Evaluating Player Performance in Different Game Contexts
por: Gu, Chaoyi, et al.
Publicado: (2024)

Model Science: getting serious about verification, explanation and control of AI systems
por: Biecek, Przemyslaw, et al.
Publicado: (2025)

Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction
por: Vishwakarma, Harit, et al.
Publicado: (2024)

Performance of Cross-Validated Targeted Maximum Likelihood Estimation
por: Smith, Matthew J., et al.
Publicado: (2024)

A Honest Cross-Validation Estimator for Prediction Performance
por: Pan, Tianyu, et al.
Publicado: (2025)

meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis
por: Sutariya, Dishantkumar, et al.
Publicado: (2025)

Position: Explain to Question not to Justify
por: Biecek, Przemyslaw, et al.
Publicado: (2024)

A Plot is Worth a Thousand Tests: Assessing Residual Diagnostics with the Lineup Protocol
por: Li, Weihao, et al.
Publicado: (2023)

Unit Commitment Predictor With a Performance Guarantee: A Support Vector Machine Classifier
por: Pourahmadi, Farzaneh, et al.
Publicado: (2023)

Detecting LLM-Generated Text with Performance Guarantees
por: Zhou, Hongyi, et al.
Publicado: (2026)

Teleodynamic Learning a new Paradigm For Interpretable AI
por: ter Horst, Enrique, et al.
Publicado: (2026)

Arbitrary-Length Generalization for Addition in a Tiny Transformer
por: Patriota, Alexandre Galvao
Publicado: (2024)

Evaluating Weather Forecasts from a Decision Maker's Perspective
por: Raeth, Kornelius, et al.
Publicado: (2025)