  We provide a catalogue of atmospheric parameters for 1,806,921 cool dwarfs
from Gaia DR3 which lie within the range covered by LAMOST cool dwarf
spectroscopic parameters: 3200 K < T_{eff}< 4300 K, -0.8 < [M/H] < 0.2 dex, and
4.5 <log{g} < 5.5 dex. Our values are derived based on Machine Learning models
trained with multi-band photometry corrected for dust. The photometric data
comprises of optical from SDSS r, i, z bands, near-infrared from 2MASS J, H, K
and mid-infrared from ALLWISE W1, W2. We used both random forest and LightGBM
machine learning models and found similar results from both with an error
dispersion of 68 K, 0.22 dex, and 0.05 dex for T_{eff}, [M/H], and log {g},
respectively. Assessment of the relative feature importance of different
photometric colors indicated W1 -- W2 as most sensitive to both T_{eff} and
log{g}, with J -- H most sensitive to [M/H]. We find that our values show a
good agreement with APOGEE, but are significantly different to those provided
as part of Gaia DR3.
