  We report the detection of 72 new pulses from the repeating fast radio burst
FRB 121102 in Breakthrough Listen C-band (4-8 GHz) observations at the Green
Bank Telescope. The new pulses were found with a convolutional neural network
in data taken on August 26, 2017, where 21 bursts have been previously
detected. Our technique combines neural network detection with dedispersion
verification. For the current application we demonstrate its advantage over a
traditional brute-force dedis- persion algorithm in terms of higher
sensitivity, lower false positive rates, and faster computational speed.
Together with the 21 previously reported pulses, this observa- tion marks the
highest number of FRB 121102 pulses from a single observation, total- ing 93
pulses in five hours, including 45 pulses within the first 30 minutes. The
number of data points reveal trends in pulse fluence, pulse detection rate, and
pulse frequency structure. We introduce a new periodicity search technique,
based on the Rayleigh test, to analyze the time of arrivals, with which we
exclude with 99% confidence pe- riodicity in time of arrivals with periods
larger than 5.1 times the model-dependent time-stamp uncertainty. In
particular, we rule out constant periods >10 ms in the barycentric arrival
times, though intrinsic periodicity in the time of emission remains plausible.
