Image de couverture de livre

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Boetius, David, Leue, Stefan, Sutter, Tobias
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks
par: Boetius, David, et autres
Publié: (2026)

BaB-prob: Branch and Bound with Preactivation Splitting for Probabilistic Verification of Neural Networks
par: Wang, Fangji, et autres
Publié: (2025)

Neural Network Verification with Branch-and-Bound for General Nonlinearities
par: Shi, Zhouxing, et autres
Publié: (2024)

E-Globe: Scalable $ε$-Global Verification of Neural Networks via Tight Upper Bounds and Pattern-Aware Branching
par: Li, Wenting, et autres
Publié: (2026)

On the Probabilistic Learnability of Compact Neural Network Preimage Bounds
par: Marzari, Luca, et autres
Publié: (2025)

SAVER: A Toolbox for Sampling-Based, Probabilistic Verification of Neural Networks
par: Sivaramakrishnan, Vignesh, et autres
Publié: (2024)

Probabilistically Tightened Linear Relaxation-based Perturbation Analysis for Neural Network Verification
par: Marzari, Luca, et autres
Publié: (2025)

Exact Verification of Graph Neural Networks with Incremental Constraint Solving
par: Liu, Minghao, et autres
Publié: (2025)

Learning to Solve Resource-Constrained Project Scheduling Problems with Duration Uncertainty using Graph Neural Networks
par: Infantes, Guillaume, et autres
Publié: (2025)

Counterexample-Guided Repair of Reinforcement Learning Systems Using Safety Critics
par: Boetius, David, et autres
Publié: (2024)

Neural Network Verification with PyRAT
par: Lemesle, Augustin, et autres
Publié: (2024)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
par: Singhi, Nishad, et autres
Publié: (2025)

Finding the DeepDream for Time Series: Activation Maximization for Univariate Time Series
par: Schlegel, Udo, et autres
Publié: (2024)

NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
par: Wang, Wenxi, et autres
Publié: (2021)

COPYCOP: Ownership Verification for Graph Neural Networks
par: Nandakumar, Rahul, et autres
Publié: (2026)

CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound
par: Anand, Akhil S, et autres
Publié: (2025)

Policy-Guided Search on Tree-of-Thoughts for Efficient Problem Solving with Bounded Language Model Queries
par: Pendurkar, Sumedh, et autres
Publié: (2026)

Bridging Neural ODE and ResNet: A Formal Error Bound for Safety Verification
par: Sayed, Abdelrahman Sayed, et autres
Publié: (2025)

KNARsack: Teaching Neural Algorithmic Reasoners to Solve Pseudo-Polynomial Problems
par: Požgaj, Stjepan, et autres
Publié: (2025)

Probabilistic ML Verification via Weighted Model Integration
par: Morettin, Paolo, et autres
Publié: (2024)

Adversarial Generative Flow Network for Solving Vehicle Routing Problems
par: Zhang, Ni, et autres
Publié: (2025)

Neural Network Approximators for Marginal MAP in Probabilistic Circuits
par: Arya, Shivvrat, et autres
Publié: (2024)

The 6th International Verification of Neural Networks Competition (VNN-COMP 2025): Summary and Results
par: Kaulen, Konstantin, et autres
Publié: (2025)

What Planning Problems Can A Relational Neural Network Solve?
par: Mao, Jiayuan, et autres
Publié: (2023)

Formal Verification of Graph Convolutional Networks with Uncertain Node Features and Uncertain Graph Structure
par: Ladner, Tobias, et autres
Publié: (2024)

Certified Training with Branch-and-Bound for Lyapunov-stable Neural Control
par: Shi, Zhouxing, et autres
Publié: (2024)

DeepCDCL: An CDCL-based Neural Network Verification Framework
par: Liu, Zongxin, et autres
Publié: (2024)

The Cost of Relaxation: Evaluating the Error in Convex Neural Network Verification
par: Papamichail, Merkouris, et autres
Publié: (2026)

Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks
par: Lee, Su Hyeong, et autres
Publié: (2025)

Beyond Either-Or Reasoning: Transduction and Induction as Cooperative Problem-Solving Paradigms
par: Zenkner, Janis, et autres
Publié: (2025)

Training Verification-Friendly Neural Networks via Neuron Behavior Consistency
par: Liu, Zongxin, et autres
Publié: (2024)

Bridging Efficiency and Safety: Formal Verification of Neural Networks with Early Exits
par: Elboher, Yizhak Yisrael, et autres
Publié: (2025)

Distributionally Robust Statistical Verification with Imprecise Neural Networks
par: Dutta, Souradeep, et autres
Publié: (2023)

Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees
par: Marzari, Luca, et autres
Publié: (2023)

Training Safe Neural Networks with Global SDP Bounds
par: Soletskyi, Roman, et autres
Publié: (2024)

Probabilistic Runtime Verification, Evaluation and Risk Assessment of Visual Deep Learning Systems
par: Torpmann-Hagen, Birk, et autres
Publié: (2025)

Causal Neural Probabilistic Circuits
par: Chen, Weixin, et autres
Publié: (2026)

Neural Approaches to SAT Solving: Design Choices and Interpretability
par: Mojžíšek, David, et autres
Publié: (2025)

Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning
par: Pourkamali-Anaraki, Farhad, et autres
Publié: (2024)

GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
par: Wang, Xiaoqi, et autres
Publié: (2022)