Results 111 to 120 of about 6,198,210 (289)
Ecological Neural Architecture Search
CoRR5 pages, 4 ...
Benjamin David Winter +1 more
openaire +3 more sources
A Study on Encodings for Neural Architecture Search
CoRR, 2020 Neural architecture search (NAS) has been extensively studied in the past few years. A popular approach is to represent each neural architecture in the search space as a directed acyclic graph (DAG), and then search over all DAGs by encoding the adjacency matrix and list of operations as a set of hyperparameters.
Colin White +3 more
openaire +4 more sources
Advanced Healthcare Materials, EarlyView.Mineralization alone does not establish a mature bone organoid. This Review integrates biological foundations, materials design, adaptive remodeling, and translational validation through the development‐to‐remodeling continuum (DRC). By separating biological functions from the evidence supporting them, the framework exposes critical gaps in current ...
Xijie Tang +4 more
wiley +1 more source
Compact Neural Architecture Search for Image Classification Using Gravitational Search Algorithm [PDF]
پژوهشهای نظری و کاربردی هوش ماشینیThis paper presents a compact neural architecture search method for image classification using the Gravitational Search Algorithm (GSA). Deep learning, through multi-layer computational models, enables automatic feature extraction from raw data at ...
Sajad Bastami +1 more
doaj +1 more source
Hierarchical neural architecture search for deep stereo matching
, 2023 To reduce the human efforts in neural network design, Neural Architecture Search (NAS) has been applied with remarkable success to various high-level vision tasks such as classification and semantic segmentation. The underlying idea for the NAS algorithm
Harandi, M +7 more
core
Advanced Materials, EarlyView.Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Neural Architecture Search for Convolutional and Transformer Deep Neural Networks [PDF]
, 2023 Deep Neural Networks (DNN) have dominated computer vision tasks during the last decade. However, in recent years, the demand for highly customized deep neural networks has increased significantly, which has made manual design of architectures a tedious
Chen, Boyu
core
Neural Architecture Search for Explainable Networks
, 2023 One of the main challenges in machine learning is providing understandable explanations for complex models. Despite outperforming humans in many tasks, machine learning models are often treated as black boxes that are difficult to interpret. Post-hoc explanation methods have been developed to create interpretable surrogate models that explain the ...
Yaoman Li, Irwin King
openaire +1 more source
Advanced Materials, EarlyView.Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source