A hybrid stacking ensemble of XGBoost, LightGBM and CatBoost with domain-informed features predicts concrete compressive ...
A brain imaging study of 146 young adults suggests that machine learning models can partly predict how strongly a person ...
Researchers have demonstrated that machine learning algorithms and symbolic regression can accurately predict the ultimate moment capacity and failure modes of long-bolted steel connections in modular ...
First joining U of T as a postdoctoral researcher, Bereyhi’s work focuses on limits and the practical aspects of machine ...
This research demonstrates a photonic quantum approach to modeling chaotic fluid dynamics, achieving low error rates with ...
MIT CSAIL's "weight-space programming" has a frontier LLM read and edit neural network weights directly, with no gradient descent. Surgical edits ended Qwen's reasoning loops, but the results come ...
FirstQFM achieves highest accuracy in financial forecasting using Quantum Reservoir Computing (QRC) on Rigetti’s ...
Automatic modulation classification (AMC) is a crucial task in modern communication systems, enabling the identification of modulation schemes in received signals. This paper presents a proposed model ...
Box ManipulationIn the history of artificial intelligence and machine learning, the determination of internal parameters ...
Physical Superintelligence announced on November 6, 2026 that an internal research system running instances of a non-public ...
Instruction tuning uses examples of instructions and desired responses to make a pretrained model more useful, controllable, ...
B.E. CSE at Osmania University (2014-2018) and M.Tech CS / AI at SSSIHL. - saikrishnavadali05/Academic-CSE-Osmania-SSSIHL ...
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