python train_hcnaf_gaussians.py --dataset gaussians_exp1 --batch_dim 64 --clip_gradnorm_max 1.0 --n_layers_flow 2 --dim_h_flow 64 --hypernet_layers 2 --norm_HW modified_weightnorm --patience 20

python train_hcnaf_gaussians.py --dataset gaussians_exp2 --batch_dim 4 --clip_gradnorm_max 0.1 --n_layers_flow 3 --dim_h_flow 200 --hypernet_layers 2 --norm_HW scaled_frobenius --patience 50

python test_hcnaf_gaussians.py --task plot --loadpath $PATH_TO_MODEL_FOLDER --loadfilename $MODEL_FILENAME

python test_hcnaf_gaussians.py --task NLL --loadpath $PATH_TO_MODEL_FOLDER --loadfilename $MODEL_FILENAME

python train_PRECOG_Carla.py --dataset PRECOG_Carla --ablation_mode All_faster_temporal --batch_size 8 --n_layers_flow 3 --dim_h_flow 100 --norm_HW modified_weightnorm --loss PNLL_output --temporal 1

python train_PRECOG_Carla.py --dataset PRECOG_Carla --ablation_mode All_faster_temporal --batch_size 4 --n_layers_flow 3 --dim_h_flow 20 --norm_HW scaled_frobenius --loss PNLL_output --temporal 1

python train_PRECOG_Carla.py --dataset PRECOG_Carla --ablation_mode No_lidar_faster_temporal --batch_size 4 --n_layers_flow 3 --dim_h_flow 100 --norm_HW modified_weightnorm --loss PNLL_output --temporal 1 --learning_rate 0.0002

python test_PRECOG_Carla.py --task plot --loadpath $PATH_TO_MODEL_FOLDER --loadfilename $MODEL_FILENAME

python test_PRECOG_Carla.py --task extra_PNLL --loadpath $PATH_TO_MODEL_FOLDER --loadfilename $MODEL_FILENAME

@InProceedings{Oh_2020_CVPR,
author = {Oh, Geunseob and Valois, Jean-Sebastien},
title = {HCNAF: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting},
booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}