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Abdou Aziz DIOP

abdouaziz

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updated a dataset 6 days ago

abdouaziz/tshi

published a dataset 6 days ago

abdouaziz/tshi

reacted to Kseniase's post with 👍 8 months ago

11 Types of JEPA Since Meta released the newest V-JEPA 2 this week, we thought it's a good time to revisit a few other interesting JEPA variants. JEPA, or Joint Embedding Predictive Architecture, a self-supervised learning framework that predicts the latent representation of a missing part of the input. Here are 11 JEPA types that you should know about: 1. V-JEPA 2 -> https://huggingface.co/papers/2506.09985 Trained on 1M+ hours of internet videos and a little bit of robot interaction data, V-JEPA 2 can watch, understand, answer questions, and help robots plan and act in physical world 2. Time-Series-JEPA (TS-JEPA) -> https://huggingface.co/papers/2406.04853 It's a time-series predictive model that learns compact, meaningful representations. A self-supervised semantic actor then uses them to generate control commands without raw data 3. Denoising JEPA (D-JEPA) -> https://huggingface.co/papers/2410.03755 Combines JEPA with diffusion techniques. By treating JEPA as masked image modeling and next-token prediction, D-JEPA generates data auto-regressively, incorporating diffusion and flow-matching losses 4. CNN-JEPA -> https://huggingface.co/papers/2408.07514 This SSL approach applies JEPA idea to CNNs using a sparse encoder, depthwise separable convolutions, and improved masking. On ImageNet-100, CNN-JEPA outperforms I-JEPA with 73.3% accuracy 5. Stem-JEPA -> https://huggingface.co/papers/2408.02514 Identifies instrument stems by mapping mixes and stems into a shared space using an encoder and predictor. It captures timbre, harmony, and rhythm for tasks like stem retrieval, alignment, and genre or key estimation 6. DMT-JEPA (Discriminative Masked Targets JEPA) -> https://huggingface.co/papers/2405.17995 Improves discriminative power by generating masked targets from semantically similar neighboring patches and uses lightweight cross-attention for aggregation Read further below👇 Also, subscribe to the Turing Post -> https://www.turingpost.com/subscribe

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