The All-Sky Automated Survey for Supernovae (ASAS-SN) is the first optical survey to monitor the entire sky, currently with a cadence of 24 hours down to 𝑔 18.5 mag. ASAS-SN has routinely operated since 2013, collecting ∼ 2,000 to over 7,500 epochs of 𝑉 and 𝑔−band observations per field to date. This work illustrates the first analysis of ASAS-SN's newer, deeper, higher cadence 𝑔−band data. From an input source list of ∼55 million isolated sources with 𝑔 < 18 mag, we identified 1.5 × 10 6 variable star candidates using a random forest classifier trained on features derived from Gaia, 2MASS and AllWISE. Using ASAS-SN 𝑔−band light curves, and an updated random forest classifier augmented with data from Citizen ASAS-SN, we classified the candidate variables into 8 broad variability types. We present a catalog of ∼116, 000 new variable stars with high classification probabilities, including ∼111, 000 periodic variables and ∼5, 000 irregular variables. We also recovered ∼263, 000 known variable stars.

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