:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Umili, Elena, Capobianco, Roberto
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2408.08622
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DeepDFA: Injecting Temporal Logic in Deep Learning for Sequential Subsymbolic Applications
by: Umili, Elena, et al.
Published: (2026)

Neural Reward Machines
by: Umili, Elena, et al.
Published: (2024)

Grounding LTL Tasks in Sub-Symbolic RL Environments for Zero-Shot Generalization
by: Pannacci, Matteo, et al.
Published: (2026)

Fully Learnable Neural Reward Machines
by: Dewidar, Hazem, et al.
Published: (2025)

DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment
by: Zhao, Gongpei, et al.
Published: (2024)

DFA-CON: A Contrastive Learning Approach for Detecting Copyright Infringement in DeepFake Art
by: Wahab, Haroon, et al.
Published: (2025)

Probabilistically Tightened Linear Relaxation-based Perturbation Analysis for Neural Network Verification
by: Marzari, Luca, et al.
Published: (2025)

Towards Probabilistic Inductive Logic Programming with Neurosymbolic Inference and Relaxation
by: Hillerstrom, Fieke, et al.
Published: (2024)

Symbol Grounding in Neuro-Symbolic AI: A Gentle Introduction to Reasoning Shortcuts
by: Marconato, Emanuele, et al.
Published: (2025)

Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks
by: Lee, Su Hyeong, et al.
Published: (2025)

Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement Learning
by: R, Shreyas S
Published: (2024)

Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees
by: Marzari, Luca, et al.
Published: (2023)

Neural Probabilistic Logic Learning for Knowledge Graph Reasoning
by: Sun, Fengsong, et al.
Published: (2024)

Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning
by: Chen, Weixin, et al.
Published: (2025)

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning
by: Zheng, Zinan, et al.
Published: (2024)

EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic
by: Verreet, Victor, et al.
Published: (2024)

Causal Neural Probabilistic Circuits
by: Chen, Weixin, et al.
Published: (2026)

Training Language Models via Neural Cellular Automata
by: Lee, Dan, et al.
Published: (2026)

Expressiveness of Multi-Neuron Convex Relaxations in Neural Network Certification
by: Mao, Yuhao, et al.
Published: (2024)

The Cost of Relaxation: Evaluating the Error in Convex Neural Network Verification
by: Papamichail, Merkouris, et al.
Published: (2026)

Probabilistic Runtime Verification, Evaluation and Risk Assessment of Visual Deep Learning Systems
by: Torpmann-Hagen, Birk, et al.
Published: (2025)

LLMs as Probabilistic Minimally Adequate Teachers for DFA Learning
by: Chen, Lekai, et al.
Published: (2024)

Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning
by: Pourkamali-Anaraki, Farhad, et al.
Published: (2024)

Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs
by: Papež, Milan, et al.
Published: (2025)

Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling
by: Halmos, Peter, et al.
Published: (2024)

SimCert: Probabilistic Certification for Behavioral Similarity in Deep Neural Network Compression
by: Li, Jingyang, et al.
Published: (2026)

Probabilistic ML Verification via Weighted Model Integration
by: Morettin, Paolo, et al.
Published: (2024)

Semantically Labelled Automata for Multi-Task Reinforcement Learning with LTL Instructions
by: Abate, Alessandro, et al.
Published: (2026)

Learning Dynamics of Deep Learning -- Force Analysis of Deep Neural Networks
by: Ren, Yi
Published: (2025)

CAX: Cellular Automata Accelerated in JAX
by: Faldor, Maxence, et al.
Published: (2024)

NeSyA: Neurosymbolic Automata
by: Manginas, Nikolaos, et al.
Published: (2024)

Neural Network Approximators for Marginal MAP in Probabilistic Circuits
by: Arya, Shivvrat, et al.
Published: (2024)

On the Probabilistic Learnability of Compact Neural Network Preimage Bounds
by: Marzari, Luca, et al.
Published: (2025)

Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
by: Chen, Weixin, et al.
Published: (2025)

Soft Learning Probabilistic Circuits
by: Ghandi, Soroush, et al.
Published: (2024)

Probabilistic Neural Circuits
by: Martires, Pedro Zuidberg Dos
Published: (2024)

Highly Parallelized Reinforcement Learning Training with Relaxed Assignment Dependencies
by: He, Zhouyu, et al.
Published: (2025)

Tractable Representation Learning with Probabilistic Circuits
by: Braun, Steven, et al.
Published: (2025)

Probabilistic Shielding for Safe Reinforcement Learning
by: Court, Edwin Hamel-De le, et al.
Published: (2025)

Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
by: Fang, Ronglong, et al.
Published: (2024)