Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network [PDF]
, 2018 Risi Kondor, Zhen Lin, Shubhendu Trivedi
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Advanced Science, EarlyView.This work presents a dispersive full‐channel Jones matrix modulation strategy using single‐layer metasurface. By synergizing wavelength dispersion engineering with elliptical polarization bases, independent control of four Jones matrix channels is achieved across multiple wavelengths.
Hairong He +10 more
wiley +1 more source
Self-learning virtual organisms in a physics simulator: on the optimal resolution of their visual system, the architecture of the nervous system and the computational complexity of the problem. [PDF]
Vavilovskii Zhurnal Genet SelektsiiZenin MS, Devyaterikov AP, Palyanov AY.
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Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
tUbeNet: a generalizable deep learning tool for 3D vessel segmentation. [PDF]
Biol Methods ProtocHolroyd NA +5 more
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Development of Convolutional Neural Nets for Κ/π Differentiation at the GlueX Experiment
, 2020 Matthew McEneaney
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High‐Conductivity Electrolytes Screened Using Fragment‐ and Composition‐Aware Deep Learning
Advanced Science, EarlyView.We present a new deep learning framework that hierarchically links molecular and functional unit attributions to predict electrolyte conductivity. By integrating molecular composition, ratios, and physicochemical descriptors, it achieves accurate, interpretable predictions and large‐scale virtual screening, offering chemically meaningful insights for ...
Xiangwen Wang +6 more
wiley +1 more source
Advanced Science, EarlyView.By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
Zhen Yang +9 more
wiley +1 more source
Diagnosis of Periodontitis via Neutrophil Degranulation Signatures Identified by Integrated scRNA-Seq and Deep Learning. [PDF]
Genes (Basel)Wu H, Huang L, Cai S, Xiong X, He Y.
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Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Advanced Science, EarlyView.Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source