Explanatory machine learning for sequential human teaching
Fuente:
arXiv
Saved in:
| Main Authors: | Ai, Lun, Langer, Johannes, Muggleton, Stephen H., Schmid, Ute |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LLM-Generated Explanations Do Not Suffice for Ultra-Strong Machine Learning
by: Ai, Lun, et al.
Published: (2025)
by: Ai, Lun, et al.
Published: (2025)
Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models
by: Ai, Lun, et al.
Published: (2024)
by: Ai, Lun, et al.
Published: (2024)
Active learning of digenic functions with boolean matrix logic programming
by: Ai, Lun, et al.
Published: (2024)
by: Ai, Lun, et al.
Published: (2024)
Can humans teach machines to code?
by: Hocquette, Céline, et al.
Published: (2024)
by: Hocquette, Céline, et al.
Published: (2024)
Causality in the human niche: lessons for machine learning
by: Lange, Richard D., et al.
Published: (2025)
by: Lange, Richard D., et al.
Published: (2025)
Compositional learning of functions in humans and machines
by: Zhou, Yanli, et al.
Published: (2024)
by: Zhou, Yanli, et al.
Published: (2024)
Simulating Petri nets with Boolean Matrix Logic Programming
by: Ai, Lun, et al.
Published: (2024)
by: Ai, Lun, et al.
Published: (2024)
A Mechanistic Explanatory Strategy for XAI
by: Rabiza, Marcin
Published: (2024)
by: Rabiza, Marcin
Published: (2024)
CoLa-DCE -- Concept-guided Latent Diffusion Counterfactual Explanations
by: Motzkus, Franz, et al.
Published: (2024)
by: Motzkus, Franz, et al.
Published: (2024)
Adaptive Data-Knowledge Alignment in Genetic Perturbation Prediction
by: Xiang, Yuanfang, et al.
Published: (2025)
by: Xiang, Yuanfang, et al.
Published: (2025)
Navigating Explanatory Multiverse Through Counterfactual Path Geometry
by: Sokol, Kacper, et al.
Published: (2023)
by: Sokol, Kacper, et al.
Published: (2023)
Practical machine learning is learning on small samples
by: Sapir, Marina
Published: (2025)
by: Sapir, Marina
Published: (2025)
Predicting human decisions with behavioral theories and machine learning
by: Plonsky, Ori, et al.
Published: (2019)
by: Plonsky, Ori, et al.
Published: (2019)
Explanatory Summarization with Discourse-Driven Planning
by: Liu, Dongqi, et al.
Published: (2025)
by: Liu, Dongqi, et al.
Published: (2025)
Concept frustration: Aligning human concepts and machine representations
by: Parisini, Enrico, et al.
Published: (2026)
by: Parisini, Enrico, et al.
Published: (2026)
Fast and Accurate Explanations of Distance-Based Classifiers by Uncovering Latent Explanatory Structures
by: Bley, Florian, et al.
Published: (2025)
by: Bley, Florian, et al.
Published: (2025)
DeepLogit: A sequentially constrained explainable deep learning modeling approach for transport policy analysis
by: Oon, Jeremy, et al.
Published: (2025)
by: Oon, Jeremy, et al.
Published: (2025)
Toward generative machine learning for boosting ensembles of climate simulations
by: Gooya, Parsa, et al.
Published: (2026)
by: Gooya, Parsa, et al.
Published: (2026)
Interpretability in Symbolic Regression: a benchmark of Explanatory Methods using the Feynman data set
by: Aldeia, Guilherme Seidyo Imai, et al.
Published: (2024)
by: Aldeia, Guilherme Seidyo Imai, et al.
Published: (2024)
Fairness under uncertainty in sequential decisions
by: Lee, Michelle Seng Ah, et al.
Published: (2026)
by: Lee, Michelle Seng Ah, et al.
Published: (2026)
Prediction is not Explanation: Revisiting the Explanatory Capacity of Mapping Embeddings
by: Herasimchyk, Hanna, et al.
Published: (2025)
by: Herasimchyk, Hanna, et al.
Published: (2025)
NEAT: Neighborhood-Guided, Efficient, Autoregressive Set Transformer for 3D Molecular Generation
by: Rose, Daniel, et al.
Published: (2025)
by: Rose, Daniel, et al.
Published: (2025)
Probing to Refine: Reinforcement Distillation of LLMs via Explanatory Inversion
by: Tan, Zhen, et al.
Published: (2026)
by: Tan, Zhen, et al.
Published: (2026)
Operating critical machine learning models in resource constrained regimes
by: Selvan, Raghavendra, et al.
Published: (2023)
by: Selvan, Raghavendra, et al.
Published: (2023)
Predicting life satisfaction using machine learning and explainable AI
by: Khan, Alif Elham, et al.
Published: (2025)
by: Khan, Alif Elham, et al.
Published: (2025)
Using machine learning for fault detection in lighthouse light sensors
by: Kampouridis, Michael, et al.
Published: (2024)
by: Kampouridis, Michael, et al.
Published: (2024)
Decoding complexity: how machine learning is redefining scientific discovery
by: Vinuesa, Ricardo, et al.
Published: (2024)
by: Vinuesa, Ricardo, et al.
Published: (2024)
survex: an R package for explaining machine learning survival models
by: Spytek, Mikołaj, et al.
Published: (2023)
by: Spytek, Mikołaj, et al.
Published: (2023)
A deep learning and machine learning approach to predict neonatal death in the context of São Paulo
by: Raihan, Mohon, et al.
Published: (2025)
by: Raihan, Mohon, et al.
Published: (2025)
Are We Merely Justifying Results ex Post Facto? Quantifying Explanatory Inversion in Post-Hoc Model Explanations
by: Tan, Zhen, et al.
Published: (2025)
by: Tan, Zhen, et al.
Published: (2025)
Concealed Adversarial attacks on neural networks for sequential data
by: Sokerin, Petr, et al.
Published: (2025)
by: Sokerin, Petr, et al.
Published: (2025)
Longitudinal Ensemble Integration for sequential classification with multimodal data
by: Susman, Aviad, et al.
Published: (2024)
by: Susman, Aviad, et al.
Published: (2024)
Shadows of quantum machine learning
by: Jerbi, Sofiene, et al.
Published: (2023)
by: Jerbi, Sofiene, et al.
Published: (2023)
Deep generative models as an adversarial attack strategy for tabular machine learning
by: Dyrmishi, Salijona, et al.
Published: (2024)
by: Dyrmishi, Salijona, et al.
Published: (2024)
Evaluating machine learning models for predicting pesticide toxicity to honey bees
by: Adamczyk, Jakub, et al.
Published: (2025)
by: Adamczyk, Jakub, et al.
Published: (2025)
Application of predictive machine learning in pen & paper RPG game design
by: Śliwa, Jolanta
Published: (2025)
by: Śliwa, Jolanta
Published: (2025)
The ecosystem of machine learning competitions: Platforms, participants, and their impact on AI development
by: Nasios, Ioannis
Published: (2026)
by: Nasios, Ioannis
Published: (2026)
Monitoring fairness in machine learning models that predict patient mortality in the ICU
by: van Schaik, Tempest A., et al.
Published: (2024)
by: van Schaik, Tempest A., et al.
Published: (2024)
The Dual Role of Abstracting over the Irrelevant in Symbolic Explanations: Cognitive Effort vs. Understanding
by: Saribatur, Zeynep G., et al.
Published: (2026)
by: Saribatur, Zeynep G., et al.
Published: (2026)
Locally Testing Model Detections for Semantic Global Concepts
by: Motzkus, Franz, et al.
Published: (2024)
by: Motzkus, Franz, et al.
Published: (2024)
Similar Items
-
LLM-Generated Explanations Do Not Suffice for Ultra-Strong Machine Learning
by: Ai, Lun, et al.
Published: (2025) -
Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models
by: Ai, Lun, et al.
Published: (2024) -
Active learning of digenic functions with boolean matrix logic programming
by: Ai, Lun, et al.
Published: (2024) -
Can humans teach machines to code?
by: Hocquette, Céline, et al.
Published: (2024) -
Causality in the human niche: lessons for machine learning
by: Lange, Richard D., et al.
Published: (2025)