Saved in:
| Main Authors: | Fossemò, Daniele, Mignosi, Filippo, Placidi, Giuseppe, Raggioli, Luca, Spezialetti, Matteo, D'Asaro, Fabio Aurelio |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.06838 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Checking Trustworthiness of Probabilistic Computations in a Typed Natural Deduction System
by: D'Asaro, Fabio Aurelio, et al.
Published: (2022)
by: D'Asaro, Fabio Aurelio, et al.
Published: (2022)
A Translation of Probabilistic Event Calculus into Markov Decision Processes
by: Xu, Lyris, et al.
Published: (2025)
by: Xu, Lyris, et al.
Published: (2025)
EGG CAPSULES OF SOME PROSOBRANCHS FROM THE PACIFIC COAST OF PANAMA
by: D'Asaro, Charles N.
Published: (1970)
by: D'Asaro, Charles N.
Published: (1970)
A Unifying Framework for Learning Argumentation Semantics
by: Mileva, Zlatina, et al.
Published: (2023)
by: Mileva, Zlatina, et al.
Published: (2023)
Weighted Assumption Based Argumentation to reason about ethical principles and actions
by: Baldi, Paolo, et al.
Published: (2025)
by: Baldi, Paolo, et al.
Published: (2025)
Does rainfall create buoyant forcing at the ocean surface?
by: Chaudhuri, Dipanjan, et al.
Published: (2025)
by: Chaudhuri, Dipanjan, et al.
Published: (2025)
Wave-induced biases in ADCP measurements from quasi-Lagrangian platforms
by: Shcherbina, Andrey Y., et al.
Published: (2024)
by: Shcherbina, Andrey Y., et al.
Published: (2024)
Learning Logic Specifications for Policy Guidance in POMDPs: an Inductive Logic Programming Approach
by: Meli, Daniele, et al.
Published: (2024)
by: Meli, Daniele, et al.
Published: (2024)
Deep Learning on Object-centric 3D Neural Fields
by: Ramirez, Pierluigi Zama, et al.
Published: (2023)
by: Ramirez, Pierluigi Zama, et al.
Published: (2023)
NuGraph2 with Explainability: Post-hoc Explanations for Geometric Neural Network Predictions
by: Voetberg, Margaret, et al.
Published: (2025)
by: Voetberg, Margaret, et al.
Published: (2025)
Self-Supervised Inductive Logic Programming
by: Patsantzis, Stassa
Published: (2025)
by: Patsantzis, Stassa
Published: (2025)
L2XGNN: Learning to Explain Graph Neural Networks
by: Serra, Giuseppe, et al.
Published: (2022)
by: Serra, Giuseppe, et al.
Published: (2022)
Inductive Learning for Possibilistic Logic Programs Under Stable Models
by: Hu, Hongbo, et al.
Published: (2025)
by: Hu, Hongbo, et al.
Published: (2025)
Differentiable Inductive Logic Programming for Fraud Detection
by: Wolfson, Boris, et al.
Published: (2024)
by: Wolfson, Boris, et al.
Published: (2024)
Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image Classification
by: Bianchi, Matteo, et al.
Published: (2024)
by: Bianchi, Matteo, et al.
Published: (2024)
LogicXGNN: Grounded Logical Rules for Explaining Graph Neural Networks
by: Geng, Chuqin, et al.
Published: (2025)
by: Geng, Chuqin, et al.
Published: (2025)
Explaining Explanations in Probabilistic Logic Programming
by: Vidal, Germán
Published: (2024)
by: Vidal, Germán
Published: (2024)
Autonomous observations enhance our ability to observe the biological carbon pump across diverse carbon export regimes
by: Shawnee Traylor, et al.
Published: (2025)
by: Shawnee Traylor, et al.
Published: (2025)
Post-hoc Part-prototype Networks
by: Tan, Andong, et al.
Published: (2024)
by: Tan, Andong, et al.
Published: (2024)
Object-Oriented Transition Modeling with Inductive Logic Programming
by: Stella, Gabriel, et al.
Published: (2026)
by: Stella, Gabriel, et al.
Published: (2026)
Satisfiability Modulo Theory Meets Inductive Logic Programming
by: Upreti, Nijesh, et al.
Published: (2025)
by: Upreti, Nijesh, et al.
Published: (2025)
An Empirical Comparison of Cost Functions in Inductive Logic Programming
by: Hocquette, Céline, et al.
Published: (2025)
by: Hocquette, Céline, et al.
Published: (2025)
Differentiable Inductive Logic Programming in High-Dimensional Space
by: Purgał, Stanisław J., et al.
Published: (2022)
by: Purgał, Stanisław J., et al.
Published: (2022)
Fuzzy Logic Function as a Post-hoc Explanator of the Nonlinear Classifier
by: Klimo, Martin, et al.
Published: (2024)
by: Klimo, Martin, et al.
Published: (2024)
Program Synthesis using Inductive Logic Programming for the Abstraction and Reasoning Corpus
by: Rocha, Filipe Marinho, et al.
Published: (2024)
by: Rocha, Filipe Marinho, et al.
Published: (2024)
From Program Logics to Language Logics
by: Cimini, Matteo
Published: (2024)
by: Cimini, Matteo
Published: (2024)
Learning Compositional Symbolic Task Rules from Demonstrations with Inductive Logic Programming
by: Borys, Oleh, et al.
Published: (2026)
by: Borys, Oleh, et al.
Published: (2026)
Understanding Pooling in Graph Neural Networks
by: Grattarola, Daniele, et al.
Published: (2021)
by: Grattarola, Daniele, et al.
Published: (2021)
RAW-Explainer: Post-hoc Explanations of Graph Neural Networks on Knowledge Graphs
by: Kubo, Ryoji, et al.
Published: (2025)
by: Kubo, Ryoji, et al.
Published: (2025)
Explaining Time Series Classifiers with PHAR: Rule Extraction and Fusion from Post-hoc Attributions
by: Mozolewski, Maciej, et al.
Published: (2025)
by: Mozolewski, Maciej, et al.
Published: (2025)
At the Edge of Putnam's Program: Limitative Results For Computable Inductive Logics
by: Mercier, Antoine, et al.
Published: (2026)
by: Mercier, Antoine, et al.
Published: (2026)
GLIDR: Graph-Like Inductive Logic Programming with Differentiable Reasoning
by: Johnson, Blair, et al.
Published: (2025)
by: Johnson, Blair, et al.
Published: (2025)
Towards Probabilistic Inductive Logic Programming with Neurosymbolic Inference and Relaxation
by: Hillerstrom, Fieke, et al.
Published: (2024)
by: Hillerstrom, Fieke, et al.
Published: (2024)
Post-hoc $α$ Hypothesis Testing and the Post-hoc $p$-value
by: Koning, Nick W.
Published: (2023)
by: Koning, Nick W.
Published: (2023)
UrbanAlign: Post-hoc Semantic Calibration for VLM-Human Preference Alignment
by: Zhang, Yecheng, et al.
Published: (2026)
by: Zhang, Yecheng, et al.
Published: (2026)
AI-augmented Automation for Real Driving Prediction: an Industrial Use Case
by: Eramo, Romina, et al.
Published: (2024)
by: Eramo, Romina, et al.
Published: (2024)
Conformal Semantic Image Segmentation: Post-hoc Quantification of Predictive Uncertainty
by: Mossina, Luca, et al.
Published: (2024)
by: Mossina, Luca, et al.
Published: (2024)
Can Input Attributions Explain Inductive Reasoning in In-Context Learning?
by: Ye, Mengyu, et al.
Published: (2024)
by: Ye, Mengyu, et al.
Published: (2024)
Explaining Black-box Language Models with Knowledge Probing Systems: A Post-hoc Explanation Perspective
by: Zhao, Yunxiao, et al.
Published: (2025)
by: Zhao, Yunxiao, et al.
Published: (2025)
Abductive Logical Rule Induction by Bridging Inductive Logic Programming and Multimodal Large Language Models
by: Peng, Yifei, et al.
Published: (2025)
by: Peng, Yifei, et al.
Published: (2025)
Similar Items
-
Checking Trustworthiness of Probabilistic Computations in a Typed Natural Deduction System
by: D'Asaro, Fabio Aurelio, et al.
Published: (2022) -
A Translation of Probabilistic Event Calculus into Markov Decision Processes
by: Xu, Lyris, et al.
Published: (2025) -
EGG CAPSULES OF SOME PROSOBRANCHS FROM THE PACIFIC COAST OF PANAMA
by: D'Asaro, Charles N.
Published: (1970) -
A Unifying Framework for Learning Argumentation Semantics
by: Mileva, Zlatina, et al.
Published: (2023) -
Weighted Assumption Based Argumentation to reason about ethical principles and actions
by: Baldi, Paolo, et al.
Published: (2025)