⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

April 1, 2012AI Communications

Challenging SMT solvers to verify neural networks

PulinaLuca TacchellaArmando

View at Publisher

Ask AI

Bookmark

Share

Abstract

In recent years, Satisfiability Modulo Theory (SMT) solvers are becoming increasingly popular in the Computer Aided Verification and Reasoning community. Used natively or as back-engines, they are ...

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

PulinaLuca et al. (2012) studied this question.

synapsesocial.com/papers/6a20123e90ba8bd81b65bb58 https://doi.org/10.5555/2350156.2350160

View at Publisher

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 related papers. Consider them for comparative context:

1Spatio-temporal deep learning framework for pedestrian intention prediction in urban traffic scenesAI Communications · Wed,
2A diversity-aware recommendation system for tutoringAI Communications · Tue,
3MAFormer: A cross-channel spatio-temporal feature aggregation method for human action recognitionAI Communications · Tue,
4Considerations on sentiment of social network posts as a feature of destructive impactsAI Communications · Tue,
5Second-order Spatial Measures Low Overlap Rate Point Cloud Registration Algorithm Based On FPFH Features1AI Communications · Fri,

More from AI Communications

Multi-feature fusion dehazing based on CycleGANFri,
Distilled insights from IBERAMIA 2022Tue,
Multimodal biometric authentication: A reviewFri,
Open-world object detection: A solution based on reselection mechanism and feature disentanglementFri,
Residual SwinV2 transformer coordinate attention network for image super resolutionTue,