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    Demo Series - Small Business Backup By Veeam

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  • 1
    JEPA

    JEPA

    PyTorch code and models for V-JEPA self-supervised learning from video

    JEPA (Joint-Embedding Predictive Architecture) captures the idea of predicting missing high-level representations rather than reconstructing pixels, aiming for robust, scalable self-supervised learning. A context encoder ingests visible regions and predicts target embeddings for masked regions produced by a separate target encoder, avoiding low-level reconstruction losses that can overfit to texture.
    Downloads: 4 This Week
    Last Update:
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  • 2
    Awesome Graph Classification

    Awesome Graph Classification

    Graph embedding, classification and representation learning papers

    A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations.
    Downloads: 1 This Week
    Last Update:
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