Overcoming Dimensional Collapse in Self-supervised Contrastive Learning for Medical Image Segmentation
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Updated
Feb 19, 2024
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dimensional-collapse
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SIGIR 2026 Short | Dimensional collapse analysis for DNNs in feature interaction models.
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Jun 10, 2026 - Python
Heuristics-free self-supervised representation learning for time series with SIGReg (LeJEPA). Disentangles time-axis collapse, positional structure, and representation richness across PatchTST, TCN, and bag-of-patches encoders. Reproducible, seeded, significance-tested.
machine-learning research deep-learning time-series pytorch transformer hydra representation-learning anomaly-detection tcn time-series-forecasting self-supervised-learning financial-time-series jepa dimensional-collapse patchtst representation-collapse lejepa sigreg
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Jun 18, 2026 - Python
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