:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Papamichail, Merkouris, Varsos, Konstantinos, Flouris, Giorgos, Marques-Silva, João
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2604.18728
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptation Procedure in Misinformation Games
by: Varsos, Konstantinos, et al.
Published: (2024)

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

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

Operator Flow Matching for Timeseries Forecasting
by: Lee, Yolanne Yi Ran, et al.
Published: (2025)

Achieving the Tightest Relaxation of Sigmoids for Formal Verification
by: Chevalier, Samuel, et al.
Published: (2024)

A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML
by: Borboudakis, Giorgos, et al.
Published: (2023)

Explainability is NOT a Game
by: Marques-Silva, Joao, et al.
Published: (2023)

Delay, Plateau, or Collapse: Evaluating the Impact of Systematic Verification Error on RLVR
by: Egashira, Kazuki, et al.
Published: (2026)

Neural Network Verification with PyRAT
by: Lemesle, Augustin, et al.
Published: (2024)

Bridging Neural ODE and ResNet: A Formal Error Bound for Safety Verification
by: Sayed, Abdelrahman Sayed, et al.
Published: (2025)

COPYCOP: Ownership Verification for Graph Neural Networks
by: Nandakumar, Rahul, et al.
Published: (2026)

CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks
by: Rao, Xuan, et al.
Published: (2022)

Aligning Evaluation with Clinical Priorities: Calibration, Label Shift, and Error Costs
by: Flores, Gerardo A., et al.
Published: (2025)

Confidence Interval Estimation of Predictive Performance in the Context of AutoML
by: Paraschakis, Konstantinos, et al.
Published: (2024)

Neural Network Verification with Branch-and-Bound for General Nonlinearities
by: Shi, Zhouxing, et al.
Published: (2024)

Towards trustable SHAP scores
by: Letoffe, Olivier, et al.
Published: (2024)

SHAP scores fail pervasively even when Lipschitz succeeds
by: Letoffe, Olivier, et al.
Published: (2024)

Locally-Minimal Probabilistic Explanations
by: Izza, Yacine, et al.
Published: (2023)

Z-Error Loss for Training Neural Networks
by: Godin, Guillaume
Published: (2025)

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

Towards LLM-guided Efficient and Interpretable Multi-linear Tensor Network Rank Selection
by: Iacovides, Giorgos, et al.
Published: (2024)

Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks
by: Dorszewski, Teresa, et al.
Published: (2024)

Influence Functions for Edge Edits in Non-Convex Graph Neural Networks
by: Heo, Jaeseung, et al.
Published: (2025)

DeepCDCL: An CDCL-based Neural Network Verification Framework
by: Liu, Zongxin, et al.
Published: (2024)

GraViti: Graph-Level Variational Autoencoders with Relaxed Permutation Invariance
by: Bresson, Roman, et al.
Published: (2026)

Distributionally Robust Statistical Verification with Imprecise Neural Networks
by: Dutta, Souradeep, et al.
Published: (2023)

A Matrix Product State Model for Simultaneous Classification and Generation
by: Mossi, Alex, et al.
Published: (2024)

Efficient & Correct Predictive Equivalence for Decision Trees
by: Marques-Silva, Joao, et al.
Published: (2025)

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound
by: Boetius, David, et al.
Published: (2024)

SAVER: A Toolbox for Sampling-Based, Probabilistic Verification of Neural Networks
by: Sivaramakrishnan, Vignesh, et al.
Published: (2024)

Training Verification-Friendly Neural Networks via Neuron Behavior Consistency
by: Liu, Zongxin, et al.
Published: (2024)

Bridging Efficiency and Safety: Formal Verification of Neural Networks with Early Exits
by: Elboher, Yizhak Yisrael, et al.
Published: (2025)

Explicit and data-Efficient Encoding via Gradient Flow
by: Flouris, Kyriakos, et al.
Published: (2024)

From SHAP Scores to Feature Importance Scores
by: Letoffe, Olivier, et al.
Published: (2024)

Delivering Inflated Explanations
by: Izza, Yacine, et al.
Published: (2023)

A survey on knowledge-enhanced multimodal learning
by: Lymperaiou, Maria, et al.
Published: (2022)

Semantic Prototypes: Enhancing Transparency Without Black Boxes
by: Menis-Mastromichalakis, Orfeas, et al.
Published: (2024)

CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment
by: Mendes, Pedro, et al.
Published: (2025)

Multi-Evidence based Fact Verification via A Confidential Graph Neural Network
by: Lan, Yuqing, et al.
Published: (2024)

BoxRL-NNV: Boxed Refinement of Latin Hypercube Samples for Neural Network Verification
by: Das, Sarthak
Published: (2025)