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ba = gene_cell.shape[1] else: ba = 5000 cell = torch.tensor(np.transpose(gene_cell), dtype=torch.float32).to(device) encoded2=train_AE(cell,ba,device) return encoded,encoded2 def train_AE(feature,ba,device): loader = data.DataLoader(feature, ba) model = AE(dim=feature.shape[1])...
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Results from the Paper Edit Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers. Methods Edit No methods listed for this paper. Add relevant methods here Contact us on: hello@paperswithcode.com . Papers With Code is...
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Deep Feature Interaction Maps (DFIM). Contribute to kundajelab/dfim development by creating an account on GitHub.
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This repository has been superseded by https://github.com/halcy/AnimeFaceNotebooks - probably have a look at that instead. DeepDanbooru Activation Maps This repository contains scripts that can be used to calculate regions of interest for recognized tags on a given image, using the DeepDanbooru ta...