Results 41 to 50 of about 109,902 (144)
A Bio‐Inspired Perspective on Materials Sustainability
Advanced Materials, EarlyView.This perspective discusses natural materials as inspiration for sustainable engineering designs and the processing of materials. First, circularity, longevity, parsimony, and activity are presented as essential material paradigms. The perspective then uses many examples of natural and technical materials to introduce principles such as oligo ...
Wolfgang Wagermaier +2 more
wiley +1 more source
Learning aligned embeddings for semi-supervised word translation using Maximum Mean Discrepancy [PDF]
arXiv, 2020 Word translation is an integral part of language translation. In machine translation, each language is considered a domain with its own word embedding. The alignment between word embeddings allows linking semantically equivalent words in multilingual contexts.
arxiv
Advanced Materials, EarlyView.The SciAgents AI model drives hypothesis generation by harnessing multi‐agent graph reasoning, extracting insights from knowledge graphs constructed from scientific papers. Each agent plays a specific role: the Ontologist defines concepts, the Scientists draft and refine proposals, and the Critic reviews.
Alireza Ghafarollahi, Markus J. Buehler
wiley +1 more source
On the Convergent Properties of Word Embedding Methods [PDF]
arXiv, 2016 Do word embeddings converge to learn similar things over different initializations? How repeatable are experiments with word embeddings? Are all word embedding techniques equally reliable? In this paper we propose evaluating methods for learning word representations by their consistency across initializations.
arxiv
Advanced Materials, EarlyView.The rise of lead halide perovskite semiconductors has enabled high‐performance LEDs with internal quantum efficiencies approaching 100%. In order to further enhance the external quantum efficiencies limited by light outcoupling effects, in this account, the strategies for reducing energy dissipation through the substrate, waveguide, and evanescent ...
Tommaso Marcato +2 more
wiley +1 more source
Think Globally, Embed Locally --- Locally Linear Meta-embedding of Words [PDF]
arXiv, 2017 Distributed word embeddings have shown superior performances in numerous Natural Language Processing (NLP) tasks. However, their performances vary significantly across different tasks, implying that the word embeddings learnt by those methods capture complementary aspects of lexical semantics.
arxiv
Advanced Materials, EarlyView.Wood and cellulose are the most abundant and important sustainable materials on the planet at the disposal to solve major societal challenges. This perspective, written for all materials scientists, highlights how breakthroughs in cellulose nanotechnology combined with functional nanomaterials can revolutionize important areas like construction ...
Mahiar Max Hamedi +5 more
wiley +1 more source
Multiplex Word Embeddings for Selectional Preference Acquisition [PDF]
arXiv, 2020 Conventional word embeddings represent words with fixed vectors, which are usually trained based on co-occurrence patterns among words. In doing so, however, the power of such representations is limited, where the same word might be functionalized separately under different syntactic relations. To address this limitation, one solution is to incorporate
arxiv
Advanced Materials, EarlyView.Reversible protonic ceramic electrochemical cells (R‐PCECs) face challenges from sluggish and unstable oxygen reduction and evolution reactions in the air electrode. This review discusses recent progress in triple‐conducting air electrodes, emphasizing mechanisms, performance factors, and design strategies, offering guidance for creating efficient and ...
Xi Chen +8 more
wiley +1 more source
Discrete Word Embedding for Logical Natural Language Understanding [PDF]
arXiv, 2020 We propose an unsupervised neural model for learning a discrete embedding of words. Unlike existing discrete embeddings, our binary embedding supports vector arithmetic operations similar to continuous embeddings. Our embedding represents each word as a set of propositional statements describing a transition rule in classical/STRIPS planning formalism.
arxiv