Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
The architecture of FOCUS. Given offline data, FOCUS learns a $p$ value matrix by KCI test and then gets the causal structure by choosing a $p$ threshold. After ...
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I will identify and discuss an important AI ...
Overview: Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...
Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...
Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...
This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
Reinforcement Learning, Explainable AI, Computational Psychiatry, Antidepressant Dose Optimization, Major Depressive Disorder, Treatment Personalization, Clinical Decision Support Share and Cite: de ...
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