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View article: Enriching Word Vectors with Subword Information
Enriching Word Vectors with Subword Information Open
Continuous word representations, trained on large unlabeled corpora are useful for many natural language processing tasks. Popular models that learn such representations ignore the morphology of words, by assigning a distinct vector to eac…
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SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules Open
SwissTargetPrediction is a web tool, on-line since 2014, that aims to predict the most probable protein targets of small molecules. Predictions are based on the similarity principle, through reverse screening. Here, we describe the 2019 ve…
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Hierarchical Text-Conditional Image Generation with CLIP Latents Open
Contrastive models like CLIP have been shown to learn robust representations of images that capture both semantics and style. To leverage these representations for image generation, we propose a two-stage model: a prior that generates a CL…
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BERTScore: Evaluating Text Generation with BERT Open
We propose BERTScore, an automatic evaluation metric for text generation. Analogously to common metrics, BERTScore computes a similarity score for each token in the candidate sentence with each token in the reference sentence. However, ins…
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Graph-based approach for airborne light detection and ranging segmentation Open
We evaluate 179 classifiers arising from 17 families (discriminant analysis, Bayesian, neural networks, support vector machines, decision trees, rule-based classifiers, boosting, bagging, stacking, random forests and other ensembles, gener…
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Image Quality Assessment through FSIM, SSIM, MSE and PSNR—A Comparative Study Open
Quality is a very important parameter for all objects and their functionalities. In image-based object recognition, image quality is a prime criterion. For authentic image quality evaluation, ground truth is required. But in practice, it i…
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Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom Open
Identifying and understanding COVID-19 vaccine hesitancy within distinct populations may aid future public health messaging. Using nationally representative data from the general adult populations of Ireland ( N = 1041) and the United King…
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Celebrity vs. Influencer endorsements in advertising: the role of identification, credibility, and Product-Endorser fit Open
In their marketing efforts, companies increasingly abandon traditional celebrity endorsers in favor of social media influencers, such as vloggers and Instafamous personalities. The effectiveness of using influencer endorsements as compared…
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Autoencoding beyond pixels using a learned similarity metric Open
We present an autoencoder that leverages learned representations to better measure similarities in data space. By combining a variational autoencoder (VAE) with a generative adversarial network (GAN) we can use learned feature representati…
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Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network Open
Despite the breakthroughs in accuracy and speed of single image super-resolution using faster and deeper convolutional neural networks, one central problem remains largely unsolved: how do we recover the finer texture details when we super…
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A general framework for quantitatively assessing ecological stochasticity Open
Significance An ecological community is a dynamic complex system with a myriad of interacting species, which are controlled by various scale-dependent deterministic and stochastic forces. With rapid advances in genomics technologies, categ…
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<i>struc2vec</i> Open
Structural identity is a concept of symmetry in which network nodes are\nidentified according to the network structure and their relationship to other\nnodes. Structural identity has been studied in theory and practice over the\npast decad…
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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models Open
Diffusion models have recently been shown to generate high-quality synthetic images, especially when paired with a guidance technique to trade off diversity for fidelity. We explore diffusion models for the problem of text-conditional imag…
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A Survey on Learning to Hash Open
Nearest neighbor search is a problem of finding the data points from the database such that the distances from them to the query point are the smallest. Learning to hash is one of the major solutions to this problem and has been widely stu…
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Dali server update Open
The Dali server (http://ekhidna2.biocenter.helsinki.fi/dali) is a network service for comparing protein structures in 3D. In favourable cases, comparing 3D structures may reveal biologically interesting similarities that are not detectable…
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METLIN: A Technology Platform for Identifying Knowns and Unknowns Open
METLIN originated as a database to characterize known metabolites and has since expanded into a technology platform for the identification of known and unknown metabolites and other chemical entities. Through this effort it has become a co…
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Siamese Recurrent Architectures for Learning Sentence Similarity Open
We present a siamese adaptation of the Long Short-Term Memory (LSTM) network for labeled data comprised of pairs of variable-length sequences. Our model is applied to assess semantic similarity between sentences, where we exceed state of t…
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A Discriminatively Learned CNN Embedding for Person Reidentification Open
In this article, we revisit two popular convolutional neural networks in person re-identification (re-ID): verification and identification models. The two models have their respective advantages and limitations due to different loss functi…
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Multiscale structural similarity for image quality assessment Open
The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore a measure of structural similarity can provide a…
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A guide to phylogenetic metrics for conservation, community ecology and macroecology Open
The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub‐disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evo…
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The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Open
While it is nearly effortless for humans to quickly assess the perceptual similarity between two images, the underlying processes are thought to be quite complex. Despite this, the most widely used perceptual metrics today, such as PSNR an…
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Image Quality Assessment: Unifying Structure and Texture Similarity Open
Objective measures of image quality generally operate by comparing pixels of a "degraded" image to those of the original. Relative to human observers, these measures are overly sensitive to resampling of texture regions (e.g., replacing on…
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ERNIE: Enhanced Representation through Knowledge Integration Open
We present a novel language representation model enhanced by knowledge called ERNIE (Enhanced Representation through kNowledge IntEgration). Inspired by the masking strategy of BERT, ERNIE is designed to learn language representation enhan…
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Comparing molecules and solids across structural and alchemical space Open
A general procedure to compare molecules and materials powers insightful representations of energy landscapes and precise machine-learning predictions of properties.
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Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction Open
Traffic prediction has drawn increasing attention in AI research field due to the increasing availability of large-scale traffic data and its importance in the real world. For example, an accurate taxi demand prediction can assist taxi com…
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Searching for Activation Functions Open
The choice of activation functions in deep networks has a significant effect on the training dynamics and task performance. Currently, the most successful and widely-used activation function is the Rectified Linear Unit (ReLU). Although va…
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SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Open
Federated Averaging (FedAvg) has emerged as the algorithm of choice for federated learning due to its simplicity and low communication cost. However, in spite of recent research efforts, its performance is not fully understood. We obtain t…
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VIRIDIC—A Novel Tool to Calculate the Intergenomic Similarities of Prokaryote-Infecting Viruses Open
Nucleotide-based intergenomic similarities are useful to understand how viruses are related with each other and to classify them. Here we have developed VIRIDIC, which implements the traditional algorithm used by the International Committe…
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Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency Open
We address the problem of adversarial attacks on text classification, which is rarely studied comparing to attacks on image classification. The challenge of this task is to generate adversarial examples that maintain lexical correctness, g…
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Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network Open
Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: lo…