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---
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: Screenshot
parameters:
negative_prompt: Identifiability of the latent space
output:
url: images/Screenshot 2024-11-29 at 02.26.15.png
base_model: ali-vilab/In-Context-LoRA
instance_prompt: Time Series, Disentanglement, Identifiability
license: apache-2.0
---
# TimeCSL
<Gallery />
## Model description
# Identifiability Guarantees For Time Series Representation via Contrastive Sparsity-inducing
Official code for the paper **Identifiability Guarantees For Time Series Representation via Contrastive Sparsity-inducing**

We define the identifiability problem for time series variable models, where factors are represented by latent slots.
We are thrilled to announce the release of 221 models, now available in the `checkpoints` folder and downloadable from [https://huggingface.co/anonymousModelsTimeCSL/TimeCSL](https://huggingface.co/anonymousModelsTimeCSL/TimeCSL). These models are part of our commitment to advancing machine learning and equipping the community with state-of-the-art tools for time series analysis. Visit the repository to explore the models and seamlessly integrate them into your projects.
Our code is available at https://anonymous.4open.science/r/TimeCSL-4320.

### Some Results


## Trigger words
You should use `Time Series` to trigger the image generation.
You should use `Disentanglement` to trigger the image generation.
You should use `Identifiability` to trigger the image generation.
## Download model
[Download](/anonymousModelsTimeCSL/TimeCSL/tree/main) them in the Files & versions tab.
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