Foundational insights, methodology reviews, and announcements from the DSTC Academic Council.

How active inference and the free energy principle establish a unified mathematical framework for self-organizing agentic AI.

A mathematical review of message passing neural networks (MPNN) in predicting quantum mechanical properties of solid-state materials.

An analysis of LSTM neural architectures and reinforcement learning protocols in load balancing and power flow scheduling.

A review of structural bioinformatics algorithms, genomic sequences, and 3D folding predictions using deep learning architectures.

How machine learning regression solvers predict missing sustainability metrics for complex industrial supply chains.
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