暂无分享,去创建一个
Michael Siebers | Johannes Rabold | Ute Schmid | Johannes Rabold | M. Siebers | U. Schmid | Ute Schmid
[1] D. Gentner,et al. Learning and Transfer: A General Role for Analogical Encoding , 2003 .
[2] Michael Siebers,et al. Please delete that! Why should I? , 2018, KI - Künstliche Intelligenz.
[3] Ute Schmid,et al. Interactive Learning with Mutual Explanations in Relational Domains , 2021, Human-Like Machine Intelligence.
[4] Andrew McCallum,et al. Introduction to Statistical Relational Learning , 2007 .
[5] Charu C. Aggarwal,et al. Efficient Data Representation by Selecting Prototypes with Importance Weights , 2017, 2019 IEEE International Conference on Data Mining (ICDM).
[6] Klaus-Robert Müller,et al. Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models , 2017, ArXiv.
[7] Brandon M. Greenwell,et al. Interpretable Machine Learning , 2019, Hands-On Machine Learning with R.
[8] Eleanor Rosch,et al. Principles of Categorization , 1978 .
[9] Wojciech Samek,et al. Explainable AI: Interpreting, Explaining and Visualizing Deep Learning , 2019, Explainable AI.
[10] Oluwasanmi Koyejo,et al. Examples are not enough, learn to criticize! Criticism for Interpretability , 2016, NIPS.
[11] Leon Sterling,et al. The Art of Prolog - Advanced Programming Techniques , 1986 .
[12] Francisco Herrera,et al. Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI , 2020, Inf. Fusion.
[13] José Hernández-Orallo,et al. The teaching size: computable teachers and learners for universal languages , 2019, Machine Learning.
[14] L. Thurstone. A law of comparative judgment. , 1994 .
[15] Carlos Guestrin,et al. "Why Should I Trust You?": Explaining the Predictions of Any Classifier , 2016, ArXiv.
[16] M J Sternberg,et al. Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming. , 1996, Proceedings of the National Academy of Sciences of the United States of America.
[17] R. Tibshirani,et al. Prototype selection for interpretable classification , 2011, 1202.5933.
[18] Seyed Mehran Kazemi,et al. RelNN: A Deep Neural Model for Relational Learning , 2017, AAAI.
[19] John L. Pollock. The ‘possible worlds’ analysis of counterfactuals , 1976 .
[20] Matthew Lease,et al. Believe it or not: Designing a Human-AI Partnership for Mixed-Initiative Fact-Checking , 2018, UIST.
[21] Tim Miller,et al. Explanation in Artificial Intelligence: Insights from the Social Sciences , 2017, Artif. Intell..
[22] Mark O. Riedl,et al. Rationalization: A Neural Machine Translation Approach to Generating Natural Language Explanations , 2017, AIES.
[23] Stephen Muggleton,et al. Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP , 2018, Machine Learning.
[24] Luc De Raedt,et al. Inductive Logic Programming: Theory and Methods , 1994, J. Log. Program..
[25] Mark E. Stickel,et al. A prolog-like inference system for computing minimum-cost abductive explanations in natural-language interpretation , 1991, Annals of Mathematics and Artificial Intelligence.
[26] Amina Adadi,et al. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI) , 2018, IEEE Access.
[27] Amit Dhurandhar,et al. Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives , 2018, NeurIPS.
[28] Hisao Tamaki,et al. OLD Resolution with Tabulation , 1986, ICLP.
[29] Joseph Jay Williams,et al. The role of explanation in discovery and generalization: evidence from category learning , 2010, ICLS.
[30] Ute Schmid,et al. A Closer Look at Structural Similarity in Analogical Transfer1 , 2002 .
[31] Patrick Henry Winston,et al. Learning structural descriptions from examples , 1970 .
[32] Chris Russell,et al. Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR , 2017, ArXiv.
[33] Ute Schmid,et al. Beneficial and harmful explanatory machine learning , 2020, Machine Learning.
[34] Sergio Gomez Colmenarejo,et al. Hybrid computing using a neural network with dynamic external memory , 2016, Nature.
[35] A. Culyer. Thurstone’s Law of Comparative Judgment , 2014 .
[36] D. Gentner,et al. PSYCHOLOGICAL SCIENCE Research Article STRUCTURAL ALIGNMENT IN COMPARISON: No Difference Without Similarity , 2022 .
[37] Herbert H. Clark,et al. Semantics: A new outline. , 1976 .
[38] Jure Leskovec,et al. Interpretable Decision Sets: A Joint Framework for Description and Prediction , 2016, KDD.