Results 131 to 140 of about 6,391,262 (321)

RSRM: Reinforcement Symbolic Regression Machine

, 2023
In nature, the behaviors of many complex systems can be described by parsimonious math equations. Automatically distilling these equations from limited data is cast as a symbolic regression process which hitherto remains a grand challenge.
Xu, Yilong, Liu, Yang, Sun, Hao
core  

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Density regression trees

, 2012
Symbolic data analysis was introduced in the last decade in order to provide a generalization of standard data analysis tools. This class of data allows each individual (or class) to take a finite set of values, or categories, intervals or distributions ...
D'AMBROSIO, ANTONIO, ARIA, MASSIMO, SICILIANO, ROBERTA   +2 more
core  

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

Discovering data‐driven microbial growth models with symbolic regression

Methods in Ecology and Evolution
Connecting mathematical models with empirically measured microbial growth has remained challenging, as numerous competing models based on different theoretical approaches can fit observations.
T. Anthony Sun, Dovydas Kičiatovas, Inga‐Katariina Aapalampi, Teemu Kuosmanen, Teppo Hiltunen, Ville Mustonen   +5 more
doaj   +1 more source

Innate Immunocompetent hiPSC‐Derived Neurospheroids Capture Early CNS Responses to rAAV

Advanced Science, EarlyView.
Knowledge of human CNS immune responses to AAV‐based gene therapies remains limited due to the lack of immune‐competent human models. Here, a hiPSC‐derived 3D neuroimmune platform integrating neurospheroids and microglia is established using stirred‐tank bioreactors.
Catarina M. Gomes, Gabriela Silva, Mafalda Aleixo, Marta Gomes, Daniel Simão, Stephan J. Holtkamp, Diana D. Lobo, Pradeep Harish, Rosalind Jenkins, Lekh N. Dahal, Rui J. Nobre, Luís de Pereira de Almeida, Mark Trautwein, Paula M. Alves, Catarina Brito   +14 more
wiley   +1 more source

Discovering equations from data: symbolic regression in dynamical systems

Journal of Physics: Complexity
The process of discovering equations from data lies at the heart of physics and in many other areas of research, including mathematical ecology and epidemiology.
Beatriz R Brum, Luiza Lober, Isolde Previdelli, Francisco A Rodrigues   +3 more
doaj   +1 more source

Decomposable Neuro Symbolic Regression

CoRR
Symbolic regression (SR) models complex systems by discovering mathematical expressions that capture underlying relationships in observed data. However, most SR methods prioritize minimizing prediction error over identifying the governing equations, often producing overly complex or inaccurate expressions.
Giorgio Morales, John W. Sheppard
openaire   +3 more sources

Charting Endocrine Progenitors Across Species and Organs

Advanced Science, EarlyView.
Endocrine progenitors give rise to the hormone‐producing cells of the pancreas and intestine. Using single‐cell multiomics and proteomics, this study compares these progenitors across species, systems, and organs, mapping the conserved and species‐specific gene regulatory networks that guide their formation.
Changying Jing, Michael Sterr, Özüm Sehnaz Caliskan, Lama Saber, Nicole Katarina Rogers, Samuel Ogden, Kei Kozawa, Christos Karampelias, Jessica Jaki, Aimée Bastidas‐Ponce, Falk Janos Farkas, Oliver Czarnecki, Osvaldo Rodrigues Pereira, Perla Cota, Valerie Vandenbempt, Diego Balboa, Anika Böttcher, Natalie Krahmer, Mohammad Lotfollahi, Julie B. Sneddon, Heiko Lickert, Mostafa Bakhti   +21 more
wiley   +1 more source