Duration: (1:7:30) ?Subscribe5835 2025-02-27T08:54:03+00:00
Model Agnostic Methods for XAI | Global v.s. Local | Permutation v.s. Surrogate Models
(8:38)
Module 1 - Lesson 4: Model Agnostic Methods
(4:18)
Explainable AI explained! | #3 LIME
(13:59)
Introduction to Explainable AI (XAI) | Interpretable models, agnostic methods, counterfactuals
(11:51)
iml: A new Package for Model-Agnostic Interpretable Machine Learning
(19:3)
3.1 Introduction to model agnostic explainability techniques
(3:55)
Interpretable Machine Learning - Local Interpretable Model-agnostic Explanations (LIME) - Pitfalls
(15:22)
Explainable machine learning (2022, 3rd lecture): Global model-agnostic methods
(1:12:14)
Model-Agnostic Meta-Learning | Lecture 82 (Part 4) | Applied Deep Learning
(3:1econd)
Model-Agnostic Meta-Learning (Continued) | Lecture 83 (Part 1) | Applied Deep Learning
(14:58)
Toward Efficient Learning: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
(24:6)
Probabilistic Model-Agnostic Meta-Learning
FeatUp: A Model-Agnostic Framework for Features at Any Resolution (ICLR 2024)
(4:58)
Model Agnostic Meta Learning (MAML) | Machine Learning
(6:36)
Interpretable Machine Learning - Local Interpretable Model-agnostic Explanations (LIME) - Examples
(10:15)
Model-Agnostic Counterfactual Explanations for Consequential Decisions
(17:43)
Model-agnostic Measure of Generalization Difficulty
(1:7:30)
Sharpening Local Interpretable Model Agnostic Explanations forDigitalPathology:Mara Graziani(HES-SO)
(16:17)
Model-agnostic vs. Model-intrinsic Interpretability for Explainable Product Search
(19:55)
Fairness-aware Model-agnostic Positive and Unlabeled Learning
(12:2)