Neural networks in high energy physics: A ten year perspective Original Research Article

A summary of neural network applications in high energy physics over the past ten years is given, including both online hardware and offline physics implementations. The emphasis is on successful applications to mainstream experimental high energy physics experiments, but includes also certain landmark historical events in the introduction of neural nets into the field. Conclusions concerning the applicability of the technique are drawn, and suggestions for possible future work are given.