Imagen de Portada

Artifact of GenBaB: Neural Network Verification with Branch-and-Bound for General Nonlinearities

Fuente: Zenodo

Guardado en:

Detalles Bibliográficos
Autores principales:	Shi, Zhouxing, Jin, Qirui, Kolter, Zico, Jana, Suman, Hsieh, Cho-Jui, Zhang, Huan
Formato:	Recurso digital
Publicado:	Zenodo 2025
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

Certified Training with Branch-and-Bound for Lyapunov-stable Neural Control
por: Shi, Zhouxing, et al.
Publicado: (2024)

Provably Bounding Neural Network Preimages
por: Kotha, Suhas, et al.
Publicado: (2023)

SoundnessBench: A Soundness Benchmark for Neural Network Verifiers
por: Zhou, Xingjian, et al.
Publicado: (2024)

Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation
por: Yang, Lujie, et al.
Publicado: (2024)

Defending LLMs against Jailbreaking Attacks via Backtranslation
por: Wang, Yihan, et al.
Publicado: (2024)

BaB-prob: Branch and Bound with Preactivation Splitting for Probabilistic Verification of Neural Networks
por: Wang, Fangji, et al.
Publicado: (2025)

Talking with Verifiers: Automatic Specification Generation for Neural Network Verification
por: Elboher, Yizhak Y., et al.
Publicado: (2026)

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics
por: Shen, Keyi, et al.
Publicado: (2024)

Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation
por: Roderick, Melrose, et al.
Publicado: (2023)

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification
por: Fukuda, Kota, et al.
Publicado: (2025)

Branch and Bound for Piecewise Linear Neural Network Verification
por: Bunel, Rudy, et al.
Publicado: (2019)

Mimetic Initialization of MLPs
por: Trockman, Asher, et al.
Publicado: (2026)

AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs
por: Akinwande, Victor, et al.
Publicado: (2024)

Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes
por: Zhou, Duo, et al.
Publicado: (2024)

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

E-Globe: Scalable $ε$-Global Verification of Neural Networks via Tight Upper Bounds and Pattern-Aware Branching
por: Li, Wenting, et al.
Publicado: (2026)

Bayesian Neural Networks with Domain Knowledge Priors
por: Sam, Dylan, et al.
Publicado: (2024)

FUSE-ing Language Models: Zero-Shot Adapter Discovery for Prompt Optimization Across Tokenizers
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)

Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning
por: Huang, Benhao, et al.
Publicado: (2026)

Why is SAM Robust to Label Noise?
por: Baek, Christina, et al.
Publicado: (2024)

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees
por: Zhang, Guanqin, et al.
Publicado: (2025)

Predicting the Performance of Black-box LLMs through Follow-up Queries
por: Sam, Dylan, et al.
Publicado: (2025)

One-Step Diffusion Distillation via Deep Equilibrium Models
por: Geng, Zhengyang, et al.
Publicado: (2023)

Diffusing Differentiable Representations
por: Savani, Yash, et al.
Publicado: (2024)

Adversarial Examples Detection with Bayesian Neural Network
por: Li, Yao, et al.
Publicado: (2021)

SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
por: Chiu, Hong-Ming, et al.
Publicado: (2025)

Prompt Recovery for Image Generation Models: A Comparative Study of Discrete Optimizers
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)

DialectGen: Benchmarking and Improving Dialect Robustness in Multimodal Generation
por: Zhou, Yu, et al.
Publicado: (2025)

AI Co-Scientist for Ranking: Discovering Novel Search Ranking Models alongside LLM-based AI Agents with Cloud Computing Access
por: Wu, Liwei, et al.
Publicado: (2026)

From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence
por: Finzi, Marc, et al.
Publicado: (2026)

Mean Flows for One-step Generative Modeling
por: Geng, Zhengyang, et al.
Publicado: (2025)

Forcing Diffuse Distributions out of Language Models
por: Zhang, Yiming, et al.
Publicado: (2024)

On Branch-and-Price for Project Scheduling
por: Kolter, Maximilian, et al.
Publicado: (2025)

The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints
por: Wang, Po-Wei, et al.
Publicado: (2017)

A Simple and Effective Pruning Approach for Large Language Models
por: Sun, Mingjie, et al.
Publicado: (2023)

Context-Parametric Inversion: Why Instruction Finetuning Can Worsen Context Reliance
por: Goyal, Sachin, et al.
Publicado: (2024)

Looking beyond the next token
por: Thankaraj, Abitha, et al.
Publicado: (2025)

Massive Activations in Large Language Models
por: Sun, Mingjie, et al.
Publicado: (2024)