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pAI/MSc: ML Theory Research with Humans on the Loop
(Center for Brains, Minds and Machines (CBMM), 2026-03-25)We present pAI/MSc3, an open-source, customizable, modular multi-agent system for academic research workflows. Our goal is not autonomous scientific ideation, nor fully automated research. It is narrower and more practical: ... -
Multiplicative Regularization Generalizes Better Than Additive Regularization
(Center for Brains, Minds and Machines (CBMM), 2025-07-02)We investigate the effectiveness of multiplicative versus additive (L2) regularization in deep neural networks, focusing on convolutional neural networks for classification. While additive methods constrain the sum of ... -
Position: A Theory of Deep Learning Must Include Compositional Sparsity
(Center for Brains, Minds and Machines (CBMM), 2025-07-02)Overparametrized Deep Neural Networks (DNNs) have demonstrated remarkable success in a wide variety of domains too high-dimensional for classical shallow networks subject to the curse of dimensionality. However, open ...
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