Results 71 to 80 of about 28,763 (261)

Few-shot Learning for Spatial Regression

CoRR, 2020
We propose a few-shot learning method for spatial regression. Although Gaussian processes (GPs) have been successfully used for spatial regression, they require many observations in the target task to achieve a high predictive performance. Our model is trained using spatial datasets on various attributes in various regions, and predicts values on ...
Tomoharu Iwata, Yusuke Tanaka 0002
openaire   +2 more sources

Few Shot Learning for Information Verification

CoRR, 2021
Information verification is quite a challenging task, this is because many times verifying a claim can require picking pieces of information from multiple pieces of evidence which can have a hierarchy of complex semantic relations. Previously a lot of researchers have mainly focused on simply concatenating multiple evidence sentences to accept or ...
Usama Khalid, Mirza Omer Beg
openaire   +2 more sources

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Few shot learning for Korean winter temperature forecasts

npj Climate and Atmospheric Science
To address the challenge of limited training samples, this study employs the model-agnostic meta-learning (MAML) algorithm along with domain-knowledge-based data augmentation to predict winter temperatures on the Korean Peninsula. While data augmentation
Seol-Hee Oh, Yoo-Geun Ham
doaj   +1 more source

Recycling of NiTi Shape Memory Alloys: Fundamental and Technological Aspects of a Vacuum Induction Melting Processing Route

Advanced Engineering Materials, EarlyView.
The present study investigates recycling of NiTi shape memory alloys via vacuum induction melting. An ingot was synthesized from elemental Ni and Ti and subjected to three subsequent remelting cycles. Remelting increases process durations and impurity levels and adversely affects microstructures and functional properties.
Sakia Sophia Noorzayee, Son Tung Mai, Sarath Menon, Braulio Gadiel Sánchez Ortega, Ralf Drautz, Alexander Kauffmann, Gunther Eggeler, Jan Frenzel   +7 more
wiley   +1 more source

A Dislocation Perspective on Strength and Toughness in Ceramics

Advanced Engineering Materials, EarlyView.
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley   +1 more source

Constellation loss: Improving the efficiency of deep metric learning loss functions for the optimal embedding of histopathological images

Journal of Pathology Informatics, 2020
Background: Deep learning diagnostic algorithms are proving comparable results with human experts in a wide variety of tasks, and they still require a huge amount of well-annotated data for training, which is often non affordable.
Alfonso Medela, Artzai Picon
doaj   +1 more source

Achieving High ON State Current through Ferroelectric Polarization‐Dependent Interfacial Resistance Switching in Undoped Orthorhombic HfO2 Films

Advanced Functional Materials, EarlyView.
Ferroelectric tunnel junction devices based on epitaxial undoped ferroelectric HfO2 films demonstrate stable switching endurance of over 106 switching cycles, low write voltages of ±3 V, 16 measured resistance states, and neuromorphic capability.
Markus Hellenbrand, Nuno Estrócio, Ji S. Kim, Babak Bakhit, Marian C. Istrate, Corneliu Ghica, Tiago Rebelo, Nives Strkalj, Abin Varghese, Bernardo Almeida, Luís S. Marques, Bipin Rajendran, Judith L. MacManus‐Driscoll, José P. B. Silva   +13 more
wiley   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Electro‐Steric Ion Confinement in Polyelectrolyte Networks for Robust Nonvolatile Artificial Synapse

Advanced Functional Materials, EarlyView.
Polyelectrolyte stoichiometry governs ion transport and retention in electrolyte‐gated synaptic transistors. A PSS‐rich network creates electro‐steric ion confinement that suppresses ion back‐diffusion and stabilizes channel doping, enabling robust nonvolatile synaptic memory, linear weight updates, and low‐energy operation.
Donghwa Lee, Jinbo Kim, Myeongjin An, Jisoo Park, Junho Sung, Eunsung Hwang, Suhwan Seok, Seong‐Min Bak, Jeonghun Kim, Eunho Lee   +9 more
wiley   +1 more source