Activity
adapt to new pytorch-lightning version
adapt to new pytorch-lightning version
linear lead time embedding works better
linear lead time embedding works better
option to use homogeneous lead times only
option to use homogeneous lead times only
different data points in a batch can have different lead times
different data points in a batch can have different lead times
add configs for vit + adaln model
add configs for vit + adaln model
adaptive layernorm for lead time conditioning model
adaptive layernorm for lead time conditioning model
test script for randomized models
test script for randomized models
randomize lead times within a batch
randomize lead times within a batch
multi-step loss with randomized lead time
multi-step loss with randomized lead time
add randomized lead time training
add randomized lead time training
implement replay buffer by optimizing last prediction step only
implement replay buffer by optimizing last prediction step only
attempt to use SphericalHarmonics positional embedding but there are …
attempt to use SphericalHarmonics positional embedding but there are …
update configs to use weigted loss by default
update configs to use weigted loss by default
add an option to use weighted loss for training
add an option to use weighted loss for training
allow scaling the attention bias
allow scaling the attention bias
add more implementations of position bias
add more implementations of position bias
option to choose attn pbaas scale
option to choose attn pbaas scale
add a new vit model with absolute positional embedding
add a new vit model with absolute positional embedding
allow using different base lead times
allow using different base lead times
update vit scratch config
update vit scratch config