Topic: "neural-network-verification"
Verified-Intelligence/alpha-beta-CROWN
alpha-beta-CROWN: An Efficient, Scalable and GPU Accelerated Neural Network Verifier (winner of VNN-COMP 2021, 2022, and 2023)
Language: Python - Size: 70.4 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 202 - Forks: 46
verivital/nnv
Neural Network Verification Software Tool
Language: MATLAB - Size: 2.77 GB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 122 - Forks: 51
dynaroars/dig
DIG is a numerical invariant generation tool. It infers program invariants or properties over (i) program execution traces or (ii) program source code. DIG supports many forms of numerical invariants, including nonlinear equalities, octagonal and interval properties, min/max-plus relations, and congruence relations.
Language: Python - Size: 80.7 MB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 41 - Forks: 6
samysweb/NCubeV
NCubeV - The Nonlinear Neural Network Verifier
Language: Jupyter Notebook - Size: 62.9 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 3 - Forks: 0
ZhongkuiMa/propdag
PropDAG is a framework to develop bound propagation approaches for neural network verification.
Language: Python - Size: 39.1 KB - Last synced at: 13 days ago - Pushed at: 13 days ago - Stars: 1 - Forks: 0
phK3/DPNeurifyFV.jl
Verification of neural networks based on input splitting and forward propagation of symbolic intervals with fresh variables.
Language: Julia - Size: 11.7 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 1
ti1uan/simplex-CROWN
Uses the simplex to propose a tighter boundary for the l1 perturbation of the convex activation function network, improving the effect of the CROWN algorithm.
Language: Python - Size: 3.1 MB - Last synced at: 4 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0
AndyVale/benchmarks_vnncomp
A reorganized collection of benchmarks from VNNCOMP since 2022, divided into three categories: fully connected, convolutional, and residual networks. Each category is available as a submodule, allowing you to download individual categories or all of them at once.
Language: Python - Size: 116 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0
AndyVale/fullyconnected_benchmarks_vnncomp
This repository contains a collection of fully connected benchmarks from VNNCOMP 2022-2024. It is designed to offer a more organized version of the existing benchmarks, making it easier to test new software. We recommend cloning the 'benchmarks_vnncomp' repository, which includes this repository as a submodule.
Size: 52.2 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0
AndyVale/convolutional_benchmarks_vnncomp
This repository contains a collection of convolutional benchmarks from VNNCOMP 2022-2024. It is designed to offer a more organized version of the existing benchmarks, making it easier to test new software. We recommend cloning the 'benchmarks_vnncomp' repository, which includes this repository as a submodule.
Size: 406 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0
AndyVale/residual_benchmarks_vnncomp
This repository contains a collection of residual benchmarks from VNNCOMP 2022-2024. It is designed to offer a more organized version of the existing benchmarks, making it easier to test new software. We recommend cloning the 'benchmarks_vnncomp' repository, which includes this repository as a submodule.
Size: 325 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0