Results 81 to 90 of about 1,249,172 (345)

Effects of stimulus and task structure on temporal perceptual learning

Scientific Reports, 2021
Our ability to discriminate temporal intervals can be improved with practice. This learning is generally thought to reflect an enhancement in the representation of a trained interval, which leads to interval-specific improvements in temporal ...
Rannie Xu, Russell M. Church, Yuka Sasaki, Takeo Watanabe   +3 more
doaj   +1 more source

Photoswitchable Conductive Metal–Organic Frameworks

Advanced Functional Materials, EarlyView.
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu, Mersad Mostaghimi, Abhinav Chandresh, Saibal Jana, Wolfgang Wenzel, Lars Heinke   +5 more
wiley   +1 more source

Prediction of premature all-cause mortality: A prospective general population cohort study comparing machine-learning and standard epidemiological approaches.

PLoS ONE, 2019
BACKGROUND:Prognostic modelling using standard methods is well-established, particularly for predicting risk of single diseases. Machine-learning may offer potential to explore outcomes of even greater complexity, such as premature death.
Stephen F Weng, Luis Vaz, Nadeem Qureshi, Joe Kai   +3 more
doaj   +1 more source

Learning to Write with Cooperative Discriminators [PDF]

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018
Recurrent Neural Networks (RNNs) are powerful autoregressive sequence models, but when used to generate natural language their output tends to be overly generic, repetitive, and self-contradictory. We postulate that the objective function optimized by RNN language models, which amounts to the overall perplexity of a text, is not expressive enough to ...
Ari Holtzman, Maxwell Forbes, Antoine Bosselut, Yejin Choi, David Golub, Jan Buys   +5 more
openaire   +2 more sources

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Perceptual learning improves discrimination but does not reduce distortions in appearance.

PLoS Computational Biology
Human perceptual sensitivity often improves with training, a phenomenon known as "perceptual learning." Another important perceptual dimension is appearance, the subjective sense of stimulus magnitude.
Sarit F A Szpiro, Charlie S Burlingham, Eero P Simoncelli, Marisa Carrasco   +3 more
doaj   +1 more source

Fronto-striatal grey matter contributions to discrimination learning in Parkinson’s disease

Frontiers in Computational Neuroscience, 2013
Discrimination learning deficits in Parkinson’s disease (PD) have been well established. Using both behavioural patient studies and computational approaches, these deficits have typically been attributed to dopamine imbalance across the basal ganglia ...
Claire eO'Callaghan, Claire eO'Callaghan, Ahmed A Moustafa, Sanne ede Wit, James M Shine, Trevor W Robbins, Simon J. G Lewis, Michael eHornberger, Michael eHornberger, Michael eHornberger, Michael eHornberger   +10 more
doaj   +1 more source

A survey on measuring indirect discrimination in machine learning [PDF]

arXiv, 2015
Nowadays, many decisions are made using predictive models built on historical data.Predictive models may systematically discriminate groups of people even if the computing process is fair and well-intentioned. Discrimination-aware data mining studies how to make predictive models free from discrimination, when historical data, on which they are built ...
arxiv  

Prototypical Contrastive Learning of Unsupervised Representations

, 2021
This paper presents Prototypical Contrastive Learning (PCL), an unsupervised representation learning method that addresses the fundamental limitations of instance-wise contrastive learning.
Hoi, Steven C. H., Li, Junnan, Xiong, Caiming, Zhou, Pan   +3 more
core  

Defects in Inorganic Mechanoluminescent Phosphors: Insights and Impacts

Advanced Functional Materials, EarlyView.
Mechanoluminescence is attracting more attention recently, and defect dominates mechanoluminescence performances. Investigating how defects work in the mechanoluminescence process is crucial for elucidating its complex luminescence mechanism. This review aims to emphasize the fundamental role of defects in mechanoluminescence, which offers an ...
Wenhao Li, Sheng Wu, Jing Ren, Puxian Xiong   +3 more
wiley   +1 more source