Results 111 to 120 of about 845,859 (278)
Advanced Materials, EarlyView.Screen gate‐based transistors are presented, enabling tunable analog sigmoid and Gaussian activations. The SA‐transistor improves MRI classification accuracy, while the GA‐transistor supports precise Gaussian kernel tuning for forecasting. Both functions are implemented in a single device, offering compact, energy‐efficient analog AI processing ...
Junhyung Cho +9 more
wiley +1 more source
MathematicsWe address the challenging application of 3D pore scale reactive flow under varying geometry parameters. The task is to predict time-dependent integral quantities, i.e., breakthrough curves, from the given geometries.
Robin Herkert +5 more
doaj +1 more source
, 2003 Bayesian methods allow for a simple and intuitive representation of the function spaces used by kernel methods. This chapter describes the basic principles of Gaussian Processes, their implementation and their connection to other kernel-based Bayesian estimation methods, such as the Relevance Vector Machine.
Smola, Alexander, Schoelkopf, Bernhard
openaire +2 more sources
Advanced Materials, EarlyView.A neuromorphic computing system exploiting opto‐ionic modulation in lead halide perovskite microcrystals demonstrates high‐dimensional reservoir dynamics with diffraction‐limited node resolution. Leveraging ultrafast excited‐state interactions, it achieves efficient computation (800 pJ/node‐operation), robustly distinguishing 4‐bit pulse sequences ...
Philipp Kollenz +7 more
wiley +1 more source
Interpretable feature interaction via statistical self-supervised learning on tabular data
Machine Learning: Science and TechnologyIn high-stakes scientific contexts, explainable AI is crucial for deriving meaningful insights from complex tabular data. A formidable challenge is ensuring both rigorous statistical guarantees and clear interpretability in feature extraction.
Xiaochen Zhang, Haoyi Xiong
doaj +1 more source
Navigating Ternary Doping in Li‐ion Cathodes With Closed‐Loop Multi‐Objective Bayesian Optimization
Advanced Materials, EarlyView.The search for advanced battery materials is pushing us into highly complex composition spaces. Here, a space with about 14 million unique combinations is efficiently explored using high‐throughput experimentation guided by Bayesian optimization with a deep kernel trained on both the Materials Project database and our data.
Nooshin Zeinali Galabi +6 more
wiley +1 more source
Recent kernel methods for interacting particle systems: first numerical results
European Journal of Applied MathematicsInteracting particle systems (IPSs) are a very important class of dynamical systems, arising in different domains like biology, physics, sociology and engineering. In many applications, these systems can be very large, making their simulation and control,
Christian Fiedler +3 more
doaj +1 more source
Recent Progress on Flexible Multimodal Sensors: Decoupling Strategies, Fabrication and Applications
Advanced Materials, EarlyView.In this review, we establish a tripartite decoupling framework for flexible multimodal sensors, which elucidates the underlying principles of signal crosstalk and their solutions through material design, structural engineering, and AI algorithms. We also demonstrate its potential applications across environmental monitoring, health monitoring, human ...
Tao Wu +10 more
wiley +1 more source
Kernel methods and their derivatives: Concept and perspectives for the earth system sciences. [PDF]
PLoS One, 2020 Johnson JE +4 more
europepmc +1 more source
Superionic Amorphous Li2ZrCl6 and Li2HfCl6
Advanced Materials, EarlyView.Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley +1 more source