✨Learning Eigenstructures of Unstructured Data Manifolds

📝 Summary:
This deep learning framework learns spectral bases directly from unstructured data, eliminating traditional operator selection and eigendecomposition. It provides a data-driven alternative for geometry processing, recovering spectral bases and eigenvalues unsupervised without explicit operator co...

🔹 Publication Date: Published on Nov 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.01103
• PDF: https://arxiv.org/pdf/2512.01103

==================================

For more data science resources:
✓ https://t.me/DataScienceT

#DeepLearning #DataScience #ManifoldLearning #GeometryProcessing #UnsupervisedLearning

✨mHC: Manifold-Constrained Hyper-Connections

📝 Summary:
Manifold-Constrained Hyper-Connections mHC resolve training instability and scalability issues of Hyper-Connections HC. mHC restores identity mapping via manifold projection and infrastructure optimization, enabling effective large-scale training with improved performance.

🔹 Publication Date: Published on Dec 31, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.24880
• PDF: https://arxiv.org/pdf/2512.24880

==================================

For more data science resources:
✓ https://t.me/DataScienceT

#MachineLearning #DeepLearning #NeuralNetworks #ManifoldLearning #AI