mAGNify - Prediction of black hole properties from learned representations of LSST-like multivariate time series of AGN
Joint reconstruction and parameter regression experiments
$pip install -e .
- Attentive neural process (Kim et al 2018)
$python magnify/train_anp.py
- Latent ODE (Rubanova et al 2019)
- Toy dataset of 1d periodic functions with varying frequency
$python magnify/train_latent_ode.py --niters 600 -n 1000 -s 50 -l 10 --dataset periodic --latent-ode --noise-weight 0.01 --regress
- Mock AGN light curves, simulated using the damped random walk model
$python magnify/train_latent_ode.py --batch-size 60 --niters 50 -n 10000 -l 20 --dataset drw --latent-ode --regress
- Latent SDE (Li et al 2020)
- Single mock AGN light curve, simulated using the damped random walk model
$pip install torchsde $python magnify/train_latent_sde_param_pred.py