Results 41 to 50 of about 8,974 (165)
Looking back to lower-level information in few-shot learning
, 2020 Humans are capable of learning new concepts from small numbers of examples. In contrast, supervised deep learning models usually lack the ability to extract reliable predictive rules from limited data scenarios when attempting to classify new examples ...
Raschka, Sebastian, Yu, Zhongjie
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International Journal of Applied Earth Observations and Geoinformation, 2023 Dwelling information is very important for various applications in humanitarian emergency response. For this, Earth observation is crucial to have spatially explicit and temporally frequent observations.
Getachew Workineh Gella +4 more
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Meta-Learning by the Baldwin Effect
, 2018 The scope of the Baldwin effect was recently called into question by two papers that closely examined the seminal work of Hinton and Nowlan. To this date there has been no demonstration of its necessity in empirically challenging tasks. Here we show that
Fernando, Chrisantha Thomas +8 more
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, 2018 The field of few-shot learning has recently seen substantial advancements. Most of these advancements came from casting few-shot learning as a meta-learning problem. Model Agnostic Meta Learning or MAML is currently one of the best approaches for few-shot learning via meta-learning.
Antoniou, Antreas +2 more
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A meta-learning approach to improving transferability for freeway traffic crash risk prediction
Digital Transportation and SafetyCrash risk prediction plays a vital role in preventing freeway traffic accidents. Due to the limited availability of crash data in some freeway sections, model transferability of crash risk prediction has become an essential topic in traffic safety ...
Chenlei Liao, Xiqun (Michael) Chen
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Labeled Memory Networks for Online Model Adaptation
, 2017 Augmenting a neural network with memory that can grow without growing the number of trained parameters is a recent powerful concept with many exciting applications.
Sarawagi, Sunita, Shankar, Shiv
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Wormhole MAML: Meta-Learning in Glued Parameter Space
, 2022 In this paper, we introduce a novel variation of model-agnostic meta-learning, where an extra multiplicative parameter is introduced in the inner-loop adaptation. Our variation creates a shortcut in the parameter space for the inner-loop adaptation and increases model expressivity in a highly controllable manner.
Chang, Chih-Jung Tracy +2 more
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Few shot learning for Korean winter temperature forecasts
npj Climate and Atmospheric ScienceTo 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
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Frontiers in Cell and Developmental Biology, 2020 Major signaling pathways, such as Notch, Hedgehog (Hh), Wnt/β-catenin and Hippo, are targeted by a plethora of physiological and pathological stimuli, ultimately resulting in the modulation of genes that act coordinately to establish specific biological ...
Sabrina Zema +5 more
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Cell segmentation by multi-resolution analysis and maximum likelihood estimation (MAMLE) [PDF]
BMC Bioinformatics, 2013 AbstractBackgroundCell imaging is becoming an indispensable tool for cell and molecular biology research. However, most processes studied are stochastic in nature, and require the observation of many cells and events. Ideally, extraction of information from these images ought to rely on automatic methods.
Ribeiro Andre S. +3 more
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