Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
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Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering
Neural Information Processing Systems
The latter usually defines the protein's key function, but cannot
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Contrastive Sampling Chains in Diffusion Models
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The code is available at Contrastive-Sampling .
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Inserting Anybody in Diffusion Models via Celeb Basis
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Stable Diffusion, to generate innovative concepts, such as the users themselves.
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Deep Fractional Fourier Transform Hu Y u,,1 Jie Huang,1 Lingzhi Li2 Man Zhou
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Our code is released publicly at https://github.com/yuhuUSTC/FRFT.
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