3 projects for "input-output model" with 2 filters applied:

  • Secure File Transfer for Windows with Cerberus by Redwood Icon
    Secure File Transfer for Windows with Cerberus by Redwood

    Protect and share files over FTP/S, SFTP, HTTPS and SCP with the #1 rated Windows file transfer server.

    Cerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
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  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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  • 1
    MATLAB Deep Learning Model Hub

    MATLAB Deep Learning Model Hub

    Discover pretrained models for deep learning in MATLAB

    Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score.
    Downloads: 0 This Week
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  • 2
    Make-A-Video - Pytorch (wip)

    Make-A-Video - Pytorch (wip)

    Implementation of Make-A-Video, new SOTA text to video generator

    Implementation of Make-A-Video, new SOTA text to video generator from Meta AI, in Pytorch. They combine pseudo-3d convolutions (axial convolutions) and temporal attention and show much better temporal fusion. The pseudo-3d convolutions isn't a new concept. It has been explored before in other contexts, say for protein contact prediction as "dimensional hybrid residual networks". The gist of the paper comes down to, take a SOTA text-to-image model (here they use DALL-E2, but the same learning...
    Downloads: 4 This Week
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  • 3
    LearningToCompare_FSL

    LearningToCompare_FSL

    Learning to Compare: Relation Network for Few-Shot Learning

    ...It includes model definitions, data loading logic, episodic training loops, and scripts that implement the N-way K-shot evaluation protocol common in few-shot research. Researchers can use this codebase as a starting point to test new ideas, modify relation modules, or transfer the approach to new datasets.
    Downloads: 0 This Week
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