Results 151 to 160 of about 188,896 (327)

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kimh, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Relationship Between Knowledge and Compliance With Safety Measures: Evidence From COVID‐19

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Compliance with health safety protocols is important for protecting public health, particularly in agricultural sectors where disease outbreaks can disrupt production and market access. Despite its economic significance, we know little about what drives protocol compliance.
Nilufer Cetik, Carola Grebitus, Lauren Chenarides   +2 more
wiley   +1 more source

Statistical Statements in Probabilistic Logic Programming

, 2022
Damiano Azzolini, Elena Bellodi, Fabrizio Riguzzi   +2 more
openalex   +2 more sources

Foreign labor, peer‐networking and agricultural efficiency in the Italian dairy sector

Agribusiness, EarlyView.
Abstract While the presence of immigrants in the agricultural sector is widely acknowledged, the empirical evidence on its economic consequences is lacking, especially from a microeconomic perspective. Using the Farm Accountancy Data Network panel data for Italian dairy farms in the period 2008–2018, the present study investigates the relationship ...
Federico Antonioli, Simone Severini, Mauro Vigani   +2 more
wiley   +1 more source

Experimental demonstration of an on-chip p-bit core based on stochastic magnetic tunnel junctions and 2D MoS2 transistors

Nature Communications
Probabilistic computing is a computing scheme that offers a more efficient approach than conventional complementary metal-oxide–semiconductor (CMOS)-based logic in a variety of applications ranging from optimization to Bayesian inference, and invertible ...
John Daniel, Zheng Sun, Xuejian Zhang, Yuanqiu Tan, Neil Dilley, Zhihong Chen, Joerg Appenzeller   +6 more
doaj   +1 more source

Probabilistic Inductive Logic Programming Based on Answer Set Programming [PDF]

, 2014
Matthias Nickles, Alessandra Mileo
openalex   +1 more source

Designing Memristive Materials for Artificial Dynamic Intelligence

Advanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

A Probabilistic Soft Logic Based Approach to Exploiting Latent and Global Information in Event Classification

, 2016
Shulin Liu, Kang Liu, Shizhu He, Jun Zhao   +3 more
openalex   +2 more sources

Convergent Deduction for Probabilistic Logic [PDF]

, 2013
Peter Haddawy, Alan M. Frisch
openalex   +1 more source