Results 81 to 90 of about 6,062,625 (214)
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Maximum Silence to Noise: Sound synthesis for responsive gestural control
Modulation synthesis has been a foundational technique in the development of electronic musical instruments since their inception. This paper presents a novel approach to ring modulation synthesis, termed Maximum Silence to Noise (MSN), along with an ...
Brown, Andrew
core +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
Synthesizing parameterized self-stabilizing rings with constant-space processes
International audienceThis paper investigates the problem of synthesizing parameterized rings that are “self-stabilizing by construction”. While it is known that the verification of self-stabilization for parameterized unidirectional rings is undecidable,
Klinkhamer, Alex, +5 more
core +1 more source
Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh +3 more
wiley +1 more source
Machine learning has digitalized heterogeneous catalysis from the top of the length scale downward: prediction at the atom and the material is now mature, yet the reactor and the process remain the open frontier. This critical review traces a decade of progress across the full catalytic value chain and asks where the next decade of impact must be won ...
Rafael Larraz, Avelino Corma
wiley +2 more sources
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Linker installation in PCN‐700 provides a unique platform for precisely modulating coordination environments within a crystalline framework. By enabling controlled incorporation of diverse linkers while maintaining structural integrity, PCN‐700 offers new opportunities to unravel the fundamental principles governing coordination chemistry, including ...
Zongsu Han, Jiatong Huo, Hong‐Cai Zhou
wiley +2 more sources
Comparative Analysis of Model‐Agnostic Explanation Methods in Materials Science
To address the critical lack of explainable artificial intelligence (XAI) benchmarks in materials science, we present a quantitative and qualitative analysis of six XAI methods applied to molecular fingerprints. Our results reveal significant discrepancies in feature importance rankings, demonstrating that the chosen explanation approach introduces ...
Anna Przybyłowska +7 more
wiley +1 more source
Benchmarking Data‐Driven Control of Octopus‐Inspired Soft Arms in Underwater Environment
Underwater soft robots present safe, compliant interaction, yet reproducible control remains scarce. This work presents an open benchmark for octopus‐inspired arms: a smooth, velocity‐diverse data‐collection scheme produces a compact dataset to train a vanilla policy.
Muhammad Sunny Nazeer +6 more
wiley +1 more source

