Add link to weights and dataset

README.md

 # Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
 [![arXiv](https://img.shields.io/badge/cs.CV-arXiv%3A2106.08285-B31B1B.svg)](https://arxiv.org/abs/2106.08285)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/ChristophReich1996/Multi-StyleGAN/blob/master/LICENSE)
+[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/multi-stylegan-towards-image-based-simulation/tflm-sequence-generation-on-tlfm-dataset)](https://paperswithcode.com/sota/tflm-sequence-generation-on-tlfm-dataset?p=multi-stylegan-towards-image-based-simulation)
 
 **[Christoph Reich*](https://github.com/ChristophReich1996), [Tim Prangemeier*](https://www.bcs.tu-darmstadt.de/bcs_team/prangemeiertim.en.jsp), [Christian Wildner](https://www.bcs.tu-darmstadt.de/bcs_team/wildnerchristian.en.jsp) & [Heinz Koeppl](https://www.bcs.tu-darmstadt.de/bcs_team/koepplheinz.en.jsp)**<br/>
 *Christoph Reich and Tim Prangemeier - both authors contributed equally
 
-## | [Project Page](https://christophreich1996.github.io/multi_stylegan) | [Paper](https://arxiv.org/abs/2106.08285) | [Dataset]() |
+## | [Project Page](https://christophreich1996.github.io/multi_stylegan) | [Paper](https://arxiv.org/abs/2106.08285) | [Dataset](https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2880?locale-attribute=en_US) |
 
 <div align="center">
   <img src="/github/latent_space_interpolation.gif"  alt="1" width = 288px height = 192px >
@@ -96,13 +97,13 @@ of [Kornia](https://kornia.github.io/) or [Torchvision](https://pytorch.org/visi
 
 ## Data
 
-**Our proposed time-lapse fluorescent microscopy is available at [this url](https://arxiv.org/pdf/2106.08285.pdf).**
+**Our proposed time-lapse fluorescent microscopy is available at [this url](https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2880?locale-attribute=en_US).**
 
 The dataset includes 9696 images structured in sequences of both brightfield and green fluorescent protein (GFP) channels at a resolution of 256 × 256. Data loader classes can be found in the python package [dataset](dataset).
 
 ## Trained Model
 
-**The checkpoint of our trained Multi-StyleGAN is available at [this url]().**
+**The checkpoint of our trained Multi-StyleGAN is available at [this url](https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2879?locale-attribute=en_US).**
 
 The checkpoint (PyTorch state dict) includes the EMA generator weights (`"generator_ema"`), the generator weights 
 (`"generator"`), the generator optimizer state (`"generator_optimizer"`), the discriminator weights (`"discriminator"`),