event classificationmachine learningword embeddingssubword modelsAutomating the detection of event mentions in online texts and their classification vis-a-vis domain-specific event type taxonomies has been acknowledged by many organisations worldwide to be of paramount importance in order to facilitate the ...
In this paper, we propose TF-ICON, a novel Training-Free Image COmpositioN framework that har- nesses the power of text-driven diffusion models for cross- domain image-guided composition. This task aims to seam- lessly integrate user-provided objects into a specif...
Two models needed to be trained in this study. The word2vec model captures high-order dependency and the GHTNet is used to predict the TF-DNA binding specificity. 2.3.1. Word2vec Model Training Word2vec is one of the commonly used models in NLP, which can learn semantic knowledge in an...
(2008). Prediction of TF target sites based on atomistic models of protein-DNA complexes. BMC bioin- formatics, 9(1), 436.V. Angarica, A. Perez, A. Vasconcelos, J. Collado-Vides, and B. Contreras-Moreira, "Prediction of tf target sites based on atomistic models of protein-dna ...
The experiments are set up onMovieLens 100KandMovieLens 1M. The results reported here are evaluated on 5-folds cross validation with random seed 0 and taken average of them. All models use default configuration. ForMovieLens 100K, the batch size is 128. As forMovieLens 1M, a quite larger dat...
Factorization models are very popular in recommendation systems because they can be used to discover latent features underlying the interactions between two different kinds of entities. There are many variations of factorization algorithms (SVD, SVD++, factorization machine, ...). When implementing them...
In contrast, TF-ICON can leverage off-the-shelf diffusion models to perform cross-domain image-guided composition without requiring additional training, finetuning, or optimization. Moreover, we introduce the exceptional prompt, which contains no information, to facilitate text-driven diffusion models ...
we provide an overview of the overall structure of the proposed lightweight model. InSection 4, we train the models and conduct comparative experiments, reporting various evaluation criteria for all models in the experiments. InSection 5, we deploy the proposed model on edge devices and perform ...
This paper proposes a common base‐model for the classical object‐based and field‐based conceptual models in GIS. The model, which is called the PGOModel or 'Parameterized Geographic Object Model', is given a formal definition by using the UML modelling language. Within the scope of the pape...
Topic models can be useful tools to discover latent topics in collections of documents. Recent studies have shown the feasibility of approach topic modeling as a clustering task. We present BERTopic, a topic model that extends this process by extracting coherent topic representation through the devel...