πŸ”¬

Algorithms for Verifying Deep Neural Networks

πŸ“… 2019
technical research breakthrough
πŸ”΅ Rare

πŸ“– Description

Algorithms for Verifying Deep Neural Networks Changliu Liu Carnegie Mellon University [email address redacted] Arnon Stanford University [email address redacted] Lazarus Stanford University [email address redacted] Christopher Strong Stanford University [email address redacted] Barrett Stanford University [email address redacted] J. Kochenderfer Stanford University [email address redacted] October 11, 2020 Abstract Deep neural networks are widely used for nonlinear function approximation, with applications ranging from computer vision to control. Although these networks involve the composition of simple arithmetic operations, it can be very challenging to verify whether a particular network satisfies certain input-output properties. This article surveys methods that have emerged recently for soundly verifying such properties. These methods borrow insights from reachability analysis, optimization, and search. We discuss fundamental differences and connections between existing alg...

πŸ“Š Game Impacts

Not verified in game

Which variables this event was proposed to move, and in which direction. The magnitudes are held in the corpus but are not shown here, because they have not been verified against the shipped game. They come from pdoom-data. They describe what an event was proposed to do, not what the shipped game does with it. Most events in the corpus are flavour: they are shown for colour and do not move any game variable. Only a small minority reach the systems below, and several of the variables listed here are not read by the game at all yet. Treat this table as a design proposal under review, not as a measurement of play. Corrections and arguments are welcome — the suggestion links at the foot of this page go straight to the data repo.

Variable Direction Condition
Research proposed: up Always
Papers proposed: up Always
Vibey Doom proposed: up Always

πŸ’­ Reactions

πŸ”¬ Safety Researcher Reaction: ⚠️ Placeholder - Needs Real Quote
"Significant technical contribution"
πŸ“° Media Reaction: ⚠️ Placeholder - Needs Real Quote
"Peer-reviewed publication"
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πŸ”— Sources

🏷️ Event Metadata

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