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UCIExperimentsConfigurations.yml
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UCIExperimentsConfigurations.yml
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power-mono-DAG:
dataset: 'power'
nb_flow: 1
b_size: 2500
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [60, 60, 60, 30]
nb_steps_dual: 30
l1: 0.
gumble_T: .5
normalizer: 'monotonic'
int_net: [100, 100, 100]
nb_steps: 20
solver: 'CC'
power-affine-DAG:
dataset: 'power'
nb_flow: 1
b_size: 2500
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [60, 60, 60, 2]
nb_steps_dual: 30
l1: 0.
gumble_T: .5
normalizer: 'affine'
power-mono-coupling:
dataset: 'power'
nb_flow: 1
b_size: 2500
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [60, 60, 60, 30]
normalizer: 'monotonic'
int_net: [100, 100, 100]
nb_steps: 20
solver: 'CC'
power-affine-coupling:
dataset: 'power'
nb_flow: 1
b_size: 2500
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [60, 60, 60, 2]
normalizer: 'affine'
power-mono-autoregressive:
dataset: 'power'
nb_flow: 1
b_size: 2500
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [60, 60, 60, 30]
normalizer: 'monotonic'
int_net: [100, 100, 100]
nb_steps: 20
solver: 'CC'
power-affine-autoregressive:
dataset: 'power'
nb_flow: 1
b_size: 2500
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [60, 60, 60, 2]
normalizer: 'affine'
gas-mono-DAG:
dataset: 'gas'
nb_flow: 1
b_size: 10000
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [80, 80, 80, 30]
nb_steps_dual: 100
l1: 0.
gumble_T: .5
normalizer: 'monotonic'
int_net: [200, 200, 200]
nb_steps: 20
solver: 'CC'
weight_decay: 1e-3
gas-affine-DAG:
dataset: 'gas'
nb_flow: 1
b_size: 10000
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [80, 80, 80, 30]
nb_steps_dual: 100
l1: 0.
gumble_T: .5
normalizer: 'affine'
weight_decay: 1e-3
gas-mono-coupling:
dataset: 'gas'
nb_flow: 1
b_size: 10000
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [80, 80, 80, 30]
normalizer: 'monotonic'
int_net: [200, 200, 200]
nb_steps: 20
solver: 'CC'
weight_decay: 1e-3
gas-affine-coupling:
dataset: 'gas'
nb_flow: 1
b_size: 10000
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [80, 80, 80, 30]
normalizer: 'affine'
weight_decay: 1e-3
gas-mono-autoregressive:
dataset: 'gas'
nb_flow: 1
b_size: 10000
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [80, 80, 80, 30]
normalizer: 'monotonic'
int_net: [200, 200, 200]
nb_steps: 20
solver: 'CC'
weight_decay: 1e-3
gas-affine-autoregressive:
dataset: 'gas'
nb_flow: 1
b_size: 10000
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [80, 80, 80, 30]
normalizer: 'affine'
weight_decay: 1e-3
hepmass-mono-DAG:
dataset: 'hepmass'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [210, 210, 210, 30]
nb_steps_dual: 25
l1: 0.
gumble_T: .5
normalizer: 'monotonic'
int_net: [200, 200, 200]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-4
hepmass-affine-DAG:
dataset: 'hepmass'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [210, 210, 210, 30]
nb_steps_dual: 25
l1: 0.
gumble_T: .5
normalizer: 'affine'
weight_decay: 1e-4
hepmass-mono-coupling:
dataset: 'hepmass'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [210, 210, 210, 30]
normalizer: 'monotonic'
int_net: [200, 200, 200]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-4
hepmass-affine-coupling:
dataset: 'hepmass'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [210, 210, 210, 30]
normalizer: 'affine'
weight_decay: 1e-4
hepmass-mono-autoregressive:
dataset: 'hepmass'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [210, 210, 210, 30]
normalizer: 'monotonic'
int_net: [200, 200, 200]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-4
hepmass-affine-autoregressive:
dataset: 'hepmass'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [210, 210, 210, 30]
normalizer: 'affine'
weight_decay: 1e-4
miniboone-mono-DAG:
dataset: 'miniboone'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [430, 430, 430, 30]
nb_steps_dual: 200
l1: 0.
gumble_T: .5
normalizer: 'monotonic'
int_net: [40, 40, 40]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-2
miniboone-affine-DAG:
dataset: 'miniboone'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [430, 430, 430, 30]
nb_steps_dual: 200
l1: 0.
gumble_T: .5
normalizer: 'affine'
weight_decay: 1e-2
miniboone-mono-coupling:
dataset: 'miniboone'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [430, 430, 430, 30]
normalizer: 'monotonic'
int_net: [40, 40, 40]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-2
miniboone-affine-coupling:
dataset: 'miniboone'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [430, 430, 430, 30]
normalizer: 'affine'
weight_decay: 1e-2
miniboone-mono-autoregressive:
dataset: 'miniboone'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [430, 430, 430, 30]
normalizer: 'monotonic'
int_net: [40, 40, 40]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-2
miniboone-affine-autoregressive:
dataset: 'miniboone'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [430, 430, 430, 30]
normalizer: 'affine'
weight_decay: 1e-2
bsds300-mono-DAG:
dataset: 'bsds300'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [630, 630, 630, 30]
nb_steps_dual: 20
l1: 0.
gumble_T: .5
normalizer: 'monotonic'
int_net: [150, 150, 150]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-4
bsds300-affine-DAG:
dataset: 'bsds300'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'DAG'
emb_net: [630, 630, 630, 30]
nb_steps_dual: 20
l1: 0.
gumble_T: .5
normalizer: 'affine'
weight_decay: 1e-4
bsds300-mono-coupling:
dataset: 'bsds300'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [630, 630, 630, 30]
normalizer: 'monotonic'
int_net: [150, 150, 150]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-4
bsds300-affine-coupling:
dataset: 'bsds300'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Coupling'
emb_net: [630, 630, 630, 30]
normalizer: 'affine'
weight_decay: 1e-4
bsds300-mono-autoregressive:
dataset: 'bsds300'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [630, 630, 630, 30]
normalizer: 'monotonic'
int_net: [150, 150, 150]
nb_steps: 20
solver: 'CCParallel'
weight_decay: 1e-4
bsds300-affine-autoregressive:
dataset: 'bsds300'
nb_flow: 1
b_size: 100
nb_epoch: 10000
conditioner: 'Autoregressive'
emb_net: [630, 630, 630, 30]
normalizer: 'affine'
weight_decay: 1e-4