Results 131 to 140 of about 405,044 (354)

Ultrasmall High‐Entropy Materials: Nanoscale Effects, Synthesis, and Mechanistic Insights

Advanced Functional Materials, EarlyView.
This review article focuses on sub‐10 nm high‐entropy materials that combine nanoscale design with complex compositions for next‐generation applications. ABSTRACT Ultrasmall high‐entropy nanomaterials (USHENMs, <10 nm) merge multicomponent chemistry with size‐dependent effects, forming a distinct class of materials with unprecedented properties.
Yueyue He, Wenbo Wang, Simon Schweidler, Yanjiao Ma, Ben Breitung, Torsten Brezesinski   +5 more
wiley   +1 more source

Probabilistic machine learning and artificial intelligence [PDF]

Nature, 2015
How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience.
openaire   +2 more sources

Oxidized MoS2‐Based Multifunctional Memristive Hardware for Energy‐Efficient mmWave Signal Processing and In‐Memory Matrix Multiplication

Advanced Functional Materials, EarlyView.
Thermally oxidized MoS2‐based radio‐frequency switches enable a multifunctional platform that unifies broadband RF switching and in‐memory computation. The device achieves a cutoff frequency of 33.2 THz with high energy efficiency and supports hardware‐aware signal processing.
Juho Son, Changwoo Pyo, Sungmoon Park, Yoongi Cho, Seungchan Lee, Myungsoo Kim   +5 more
wiley   +1 more source

Artificial Intelligence

, 2012
This saylor course introduces the field of artificial intelligence (AI). Materials on AI programming,logic,search,game playing,machine learning,natural language understanding and robotics introduce the student to AI methods and techniques,their ...
The Saylor Foundation
core  

Development of a Deep-Learning-Based Artificial Intelligence Tool for Differential Diagnosis between Dry and Neovascular Age-Related Macular Degeneration

, 2020
The use of deep-learning-based artificial intelligence (AI) is emerging in ophthalmology, with AI-mediated differential diagnosis of neovascular age-related macular degeneration (AMD) and dry AMD a promising methodology for precise treatment strategies ...
Sun Mi Gu, Tae-Young Heo, Kyoung Min Kim, Hyun Kyu Min, Jung Kee Min, Jaesuk Yun, Jae Hyun Kim   +6 more
core   +1 more source

Application of Ibuprofen Sodium Dihydrate for Thermochemical Energy Storage

Advanced Functional Materials, EarlyView.
Ibuprofen sodium dihydrate is introduced as a durable organic salt hydrate for low‐temperature thermochemical energy storage, operating within 60°C–110°C with high energy density. At the material level, it delivers ∼99.9% cycling efficiency over 150 cycles without deliquescence, enabled by a dual energy‐storage mechanism coupling dehydration and phase ...
Kavin Chakravarthy Thangaraj, Hannah F. Chang, Shannon J. Lee, Mark E. Bowden, J. David Bazak, Vaithiyalingam Shutthanandan, Venkateshkumar Prabhakaran, Xiao Zhang, David M. Reed, Ajay S. Karakoti, Vijayakumar Murugesan   +10 more
wiley   +1 more source

NewsFinder: Automating an Artificial Intelligence News Service

, 2011
NewsFinder automates the steps involved in finding, select- ing and publishing news stories that meet subjective judgments of relevance and interest to the Artificial Intelligence community. NewsFinder combines a broad search with AI-specific filters and
Dong, Liang, Smith, Reid, Buchanan, Bruce   +2 more
core   +1 more source

The CHREST architecture of cognition: The role of perception in general intelligence [PDF]

, 2010
This material is posted here with the permission of the publishers.This paper argues that the CHREST architecture of cognition can shed important light on developing artificial general intelligence. The key theme is that 'cognition is perception'.
Peter Lane, Lane, Peter C.R., Fernand Gobet, Gobet, F., Gobet, Fernand, Lane, P, Lane, P.C.R., Gobet, F   +7 more
core   +1 more source

Thermally Pre‐Formed Reconfigurable Resistive Random‐Access Memory Crossbar Arrays: A Dual‐Mode Platform for Robust Physically Unclonable Functions and In‐Memory Computing

Advanced Functional Materials, EarlyView.
A reconfigurable RRAM platform utilizing thermally pre‐formed filaments (TPFs) is developed to realize robust hardware security. By exploiting the thermodynamic stochasticity of TPFs, exceptionally reliable physically unclonable functions (PUFs) are achieved.
Seongbin Kwon, Taewon Lee, Dohyeong Kim, Sungmin Hwang, Sungjoon Kim   +4 more
wiley   +1 more source

Few-Shot Bayesian Imitation Learning with Logical Program Policies

, 2020
Humans can learn many novel tasks from a very small number (1–5) of demonstrations, in stark contrast to the data requirements of nearly tabula rasa deep learning methods.
Pack Kaelbling, Leslie, Tenenbaum, Josh, Allen, Kelsey R, Silver, Tom, Lew, Alex K., Lew, Alex K, Allen, Kelsey R.   +6 more
core   +1 more source