Results 121 to 130 of about 1,338,246 (278)

Breaking the Surface: Buoyant Metal–Polymer Open–Cell Hybrid Lattice Metamaterials

Advanced Materials, EarlyView.
Open‐cell metal–polymer lattice metamaterials that defy sinking. (a) Injection process of the polyurethane (PU) foam into the titanium (Ti‐6Al‐4V) hollow‐strut lattice creating the open‐cell Ti‐6Al‐4V+PU hybrid lattice, (b) flotation test of a hybrid lattice specimen, and (c) a digital representation and experimental validation of a marine buoy ...
Jordan Noronha, Joey Tallon, Raad Omar, Jason Dash, Andrey Molotnikov, Martin Leary, Milan Brandt, Ma Qian   +7 more
wiley   +1 more source

Artificial Intelligence Meets Micro/Nanorobotics

Advanced Materials, EarlyView.
Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever, Minitha Cherukutty Ramakrishnan, Ian Kuula Ross, Ivan Zelinka, Hamed Shahsavan, Michal Otyepka, Martin Pumera   +6 more
wiley   +1 more source

Moiré‐Induced Symmetry Breaking of Charge Order in van der Waals Heterostructures

Advanced Materials, EarlyView.
A uniaxial moiré potential in misfit (MS)1+δTaS2 heterostructures selectively reshape charge order: the embedded 1H‐TaS2 layer hosts an incommensurate charge‐density wave, fragmented into nanometer domains and stripped of threefold symmetry. Superconductivity, however, remains uniform and fully gapped, revealing heterosymmetry stacking as a selective ...
Sandra Sajan, Laura Pätzold, Tarushi Agarwal, Clara Pfister, Haojie Guo, Sisheng Duan, P. V. Sruthibhai, Mariana Rossi, Maria N. Gastiasoro, Sara Barja, Ravi P. Singh, Tim Wehling, Miguel M. Ugeda   +12 more
wiley   +1 more source

Interpolation, growth conditions, and stochastic gradient descent

, 2020
Current machine learning practice requires solving huge-scale empirical risk minimization problems quickly and robustly. These problems are often highly under-determined and admit multiple solutions which exactly fit, or interpolate, the training data ...
Mishkin, Aaron
core   +1 more source

Exact Discrete Stochastic Simulation With Deep-Learning-Scale Gradient Optimization. [PDF]

Adv Sci (Weinh)
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Vilar JMG, Saiz L.
europepmc   +2 more sources

Stochastic Gradient Descent with Strategic Querying

2025 IEEE 64th Conference on Decision and Control (CDC)
18 pages, 2 figures. Accepted to IEEE Conference on Decision and Control (CDC) 2025.
Nanfei Jiang, Hoi-To Wai, Mahnoosh Alizadeh   +2 more
openaire   +3 more sources

Extreme Bond Ionicity in Mg─Te Chalcogenides for Ultrathin Low Voltage Selector‐Only Memory beyond the Leakage Scaling Limit

Advanced Materials, EarlyView.
Mg─Te chalcogenides address the leakage scaling trade‐off in ultrathin selector‐only memory. Structural partitioning in multiphase Mg─Te, combined with highly ionic Mg─Te bonding and Hf interfacial engineering, supports reliable 5 nm thickness operation at low write voltage with suppressed leakage current, narrow threshold voltage distributions, 10 ns ...
Yoori Seo, Dongmin Kim, Yu Bin Park, Jangseop Lee, Tae Hoon Lee, Hyunsang Hwang   +5 more
wiley   +1 more source

Scaling of hardware-compatible perturbative training algorithms

APL Machine Learning
In this work, we explore the capabilities of multiplexed gradient descent (MGD), a scalable and efficient perturbative zeroth-order training method for estimating the gradient of a loss function in hardware and training it via stochastic gradient descent.
B. G. Oripov, A. Dienstfrey, A. N. McCaughan, S. M. Buckley   +3 more
doaj   +1 more source

Volatile Memristive Devices With Tunable Temporal Dynamics For Event‐Based Sensing

Advanced Materials, EarlyView.
Tunable volatile memristive devices can serve various neural‐inspired tasks that require different time windows of information retention. The ionic‐based volatility of the presented Pt/a‐STO/TaOx/Ta device stack can be reproducibly and controllably tuned in multiple ways.
Dimitrios Spithouris, Johannes Hellwig, Hugh Greatorex, Clemens Wittberg, Panagiotis Koutsogiannis, César Magén, Elisabetta Chicca, Regina Dittmann   +7 more
wiley   +1 more source

A novel deep learning technique for medical image analysis using improved optimizer

Health Informatics Journal
Application of Convolutional neural network in spectrum of Medical image analysis are providing benchmark outputs which converges the interest of many researchers to explore it in depth.
Vertika Agarwal, MC Lohani, Ankur Singh Bist   +2 more
doaj   +1 more source