Results 221 to 230 of about 3,554 (301)

Generating the Critical Ising Model via SRGAN: A Schramm-Loewner Evolution Analysis from a Geometric Deep Learning Perspective. [PDF]

Entropy (Basel)
Yang Y, Li W, Wang Y, Liu Z, Tuo K.
europepmc   +1 more source

Data‐Driven High‐Throughput Volume Fraction Estimation From X‐Ray Diffraction Patterns

Advanced Intelligent Discovery, EarlyView.
Long exposure times and the need for manual evaluation limit the use of X‐ray diffraction in high‐throughput applications. This study presents a data‐driven approach addressing both issues. HiVE (a method for High‐throughput Volume fraction Estimation) performs composition estimation for high‐noise XRD patterns produced using polychromatic emission ...
Hawo H. Höfer, André Orth, Robert Wang, Ben Breitung, Simon Schweidler, Jasmin Aghassi‐Hagmann, Markus Reischl   +6 more
wiley   +1 more source

Marginally Interpretable Spatial Logistic Regression With Bridge Processes. [PDF]

Stat Med
Lee CJ, Dunson DB.
europepmc   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Takens-Based Kernel Transfer Entropy Connectivity Network for Motor Imagery Classification. [PDF]

Sensors (Basel)
Gomez-Rivera A, Álvarez-Meza AM, Cárdenas-Peña D, Orozco-Gutierrez A.   +3 more
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Kernel-DMD for multiome data integration and control. [PDF]

PLoS Comput Biol
Pierides I, Kramml HM, Waldherr S, Weckwerth W.   +3 more
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Bridging the gap between models based on ordinary, delayed, and fractional differentials equations through integral kernels. [PDF]

Proc Natl Acad Sci U S A
Zeraick Monteiro N, Weber Dos Santos R, Rodrigues Mazorche S.   +2 more
europepmc   +1 more source

Reproducing Kernel Functions

, 2018
Ali Akgül, Esra Karatas Akgül
openaire   +2 more sources