Author

Jacob Kang

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#machine learning Preprint Sep 2026

Beyond Gaussian Assumptions: Distribution-Aware Channel Capacity for Effective Connectivity

A distribution-aware, information-theoretic measure of effective connectivity based on channel capacity under general residual distributions based on normalizing flows is introduced, and a principled distribution-aware framework for effective-connectivity estimation beyond Gaussian residual modeling is established.

Jia-Nan Jian, Jacob Kang, Nurahmed Multezem et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Large Distant Gradients Need Not Be Reliable: reliability-weighted credit assignment for long-horizon autoregressive forecasting

It is shown that distant gradients can grow even as their SNR falls, and that Internal-DW reduces error in recovering predictable gradient signals and improves forecasting, and that retaining long-horizon supervision does not require trusting every backward contribution equally.

Jun-Hao Zhao, David Michael Simberg, Jacob Kang et al. · 0 citations