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laplace-autoencoders-checkpoints
keyvanatt/laplace-autoencoders-checkpoints
laplace-autoencoders-checkpoints is a machine learning model from keyvanatt. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Trained checkpoints (autoencoders and surrogates) for every configuration in the paper.
Access
Public
Updated Oct 5, 2026
Repo size
10.2 GB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.ckpt6.7 GB · 75%
At a glance
- License
- mit
- Access
- Public
- Created
- Jun 29, 2026
- Updated
- Oct 5, 2026
- SHA
- eba82d5b
Model card
From the Hugging Face model README
Laplace autoencoders: checkpoints
Trained checkpoints (autoencoders and surrogates) for every configuration in the paper.
Download
hf download keyvanatt/laplace-autoencoders-checkpoints --local-dir checkpoints
Usage
from laplace_surrogate.inference.pipeline import InferencePipeline
pipe = InferencePipeline.from_checkpoint('checkpoints/LLAEModel__llae_ld64_K16_g0.01__t4h2.ckpt')
U_pred = pipe.predict([[k, A, C]]) # (B, Nt, N, N) float32
Naming
- AE:
slae_ld{latent_dim}_K{K}_g{gamma}[_ol],llae_ld{latent_dim}_K{K}_g{gamma}[_ll],dlrom_ld{latent_dim}_Nt{Nt} - Surrogate:
{ModelClass}__{ae_stem}__t{n_trunk}h{n_head}[_ksvd{k}|_rs{r_s}rz{r_z}].ckpt(ModelClass∈SLAEModel,LLAEModel,SLAESVDModel,LLAESVDModel,SLAETuckerModel,LLAETuckerModel,DLROMModel)
- License
- mit
- Created
- Jun 29, 2026
- Updated
- Oct 5, 2026