Results 171 to 180 of about 6,391,262 (321)

Scalable Neural Symbolic Regression using Control Variables [PDF]

Symbolic regression (SR) is a powerful technique for discovering the analytical mathematical expression from data, finding various applications in natural sciences due to its good interpretability of results.
Qi, Hairong, Zhao, Hongjue, Chu, Xieting, Xu, Enze, Chen, Minghan, Shao, Huajie   +5 more
core   +1 more source

scTIDE: Deciphering Critical Transitions Through Cell‐Perturbed Manifold Graphs and Optimal Transport Conditional Flow Matching

Advanced Science, EarlyView.
scTIDE identifies single‐cell tipping points by combining manifold‐based graph representations with optimal‐transport conditional flow matching, which preserves intrinsic topology and models distributional dynamics. It supports critical‐transition detection at individual‐cell resolution, prediction of unseen cells, and dimensionality reduction and ...
Jiayuan Zhong, Bowen Niu, Yongbo Yu, Shiyang Nie, Xuerong Gu, Pei Chen, Rui Liu   +6 more
wiley   +1 more source

Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

Advanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park, Yeongje Lee, Sunho Jeong, Eungkyu Lee   +3 more
wiley   +1 more source

Closing the Empirical Loop: Autonomous AI Agents Conduct End‐to‐end Research With Human Participants

Advanced Science, EarlyView.
A multi‐agent AI system autonomously executes the complete scientific workflow, from hypothesis to manuscript, across three psychological studies involving 288 participants. The system designs experiments, collects real world data, develops analysis pipelines, and writes manuscripts with theoretical rigor comparable to experienced researchers.
Gabrielle Wehr, Reuben Rideaux, Amaya J. Fox, David R. Lightfoot, Jason Tangen, Jason B. Mattingley, Shane E. Ehrhardt   +6 more
wiley   +1 more source

Auditable unit-aware thresholds in symbolic regression via logistic-gated operators. [PDF]

iScience
Deng O, Cong R, Xu J, Nishimura S, Ogihara A, Jin Q.   +5 more
europepmc   +1 more source

Pasta, a Versatile Transcriptomic Clock, Maps the Chemical and Genetic Determinants of Aging and Rejuvenation

Advanced Science, EarlyView.
Pasta is a transcriptomic aging clock built on an age‐shift learning framework and trained on 17 000 samples across 21 datasets. It accurately predicts relative biological age across tissues, platforms, and species, captures stemness‐to‐senescence transitions, and identifies age‐modulatory perturbations.
Jérôme Salignon, Maria Tsiokou, Patricia Marqués, Enriqueta Rodríguez‐Diaz, Hazel Ang, Federico Pietrocola, Christian G. Riedel   +6 more
wiley   +1 more source

Dimensionally Consistent Formation Pressure Prediction from Borehole Sensing Data Using Pressure Ratio Symbolic Regression. [PDF]

Sensors (Basel)
Zhao C, Zhang M, Zhou L, Wang J, Kou W, Liu G.   +5 more
europepmc   +1 more source

Modulating Calcium Homeostasis via a Biomimetic Scaffold to Rescue Diabetic Ischemic Wounds

Advanced Science, EarlyView.
This strategy addresses impaired microcirculation and loss of extracellular matrix (ECM) guidance in diabetic wound healing. Musc@CP, a nanofibrous dressing combining an ECM‐mimetic chitosan‐pullulan scaffold with muscone, enhances perfusion by attenuating intracellular Ca2+ overload‐associated endothelial dysfunction.
Xiang Zheng, Mingmei Li, Jianjun Jiang, Yongchao Wang, Yaru Jia, Weilun Sun, Yi Yao, Pengli Gao, Linhua Zhang, Qi Guo, Guang Jia, Xing‐Jie Liang, Dunwan Zhu, Jinchao Zhang, Fangzhou Li   +14 more
wiley   +1 more source

Moving from table to graph in physics-informed spatio-temporal symbolic regression. [PDF]

Sci Rep
Lazebnik T, Liberzon A.
europepmc   +1 more source

Dynamic Grammar Pruning for Program Size Reduction in Symbolic Regression. [PDF]

SN Comput Sci, 2023
Ali MS, Kshirsagar M, Naredo E, Ryan C.
europepmc   +1 more source