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1861
Bitter-RF: A random forest machine model for recognizing bitter peptides
Published 2023-01-01“…Bitter-RF covers more comprehensive and extensive information by integrating 10 features extracted from the bitter peptides and achieves better results than the latest generation model on independent validation set.ResultsThe proposed model can improve the accurate classification of bitter peptides (AUROC = 0.98 on independent set test) and enrich the practical application of RF method in protein classification tasks which has not been used to build a prediction model for bitter peptides.DiscussionWe hope the Bitter-RF could provide more conveniences to scholars for bitter peptide research.…”
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Article -
1862
Beyond Gaussian Noise: A Generalized Approach to Likelihood Analysis with Non-Gaussian Noise
Published 2023-01-01“…We use diffusion generative models to estimate the gradient of the probability density of noise with respect to data elements. …”
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1863
Unsupervised Anomaly Video Detection via a Double-Flow ConvLSTM Variational Autoencoder
Published 2022-01-01“…Variational autoencoder (VAE), as one of the typical deep generative models, gets increasingly popular in unsupervised anomaly detection. …”
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1864
Energy Theft Detection Model Based on VAE-GAN for Imbalanced Dataset
Published 2023-01-01“…The proposed model is simulated on the practical dataset for comparing with various generative models to evaluate their performance. From simulation results, it is confirmed that the proposed model outperforms the other existing models. …”
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1865
Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
Published 2023-01-01“…Powerful open-source models are freely available, and user-friendly tools that democratize access to generative models are proliferating. ChatGPT, which was released shortly after the first edition of this survey, epitomizes these trends. …”
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1866
Detailed Reaction Mechanism for 350–400 °C Pyrolysis of an Alkane, Aromatic, and Long-Chain Alkylaromatic Mixture
Published 2022“…To showcase the advancements that have been made in automatic generation of large mechanisms, we constructed such a model for a three-component mixture containing species with up to 18 carbon atoms. The generated model is able to predict many of the major and minor products with relatively high accuracy against gold-tube batch pyrolysis data collected for this system. …”
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1867
Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning
Published 2022“…To address this issue, we adapt sampling tools built upon machine learning-based generative modeling to the materials space by transforming them into the semi-grand canonical ensemble. …”
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1868
DLVGen: a dual latent variable approach to personalized dialogue generation
Published 2022“…Typically, personalized dialogue generation models involve conditioning the generated response on the dialogue history and a representation of the persona/personality of the interlocutor. …”
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Conference Paper -
1869
Building a large-scale dataset for audio-conditioned dance motion synthesis
Published 2022“…Generative models for audio-conditioned dance motion synthesis map music features to dance movements. …”
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Thesis-Master by Research -
1870
Optimization of protein extraction from freeze dried fish waste using response surface methodology (RSM)
Published 2008“…Response surface methodology (RSM) was used to study the effect of independent variables, namely time (30-60 minutes), pH (7-11), rotation speed (100-300 rpm), and NaOH: substrate ratio (1-3) on protein extraction from FD-FW. From RSM-generated model, the optimum conditions for extraction of protein from FD-FW were identified to be at pH 10.56 in 48.61 minutes reaction time, with rotation speed of 104.77 rpm and NaOH: substrate ratio of 1.54. …”
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1871
Dual phase role of composite adsorbents made from cockleshell and natural zeolite in treating river water
Published 2017“…Based on the results, the composite adsorbent was fitted better with Yoon-Nelson and Thomas model rather than Adam-Bohart model. The generated models were able to characterize the adsorption process using composite adsorbent in the ECPS column system.…”
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1872
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1873
Towards efficient and robust reinforcement learning via synthetic environments and offline data
Published 2023“…Leveraging recent advances in diffusion generative models, our approach outperforms and is composable with standard data augmentation, and is particularly effective in low-data regimes. …”
Thesis -
1874
Motion control algorithm development and testing for a free-piston engine generator
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Research Report -
1875
The Effect of Enhancing Unemployment Benefits in Korea: Wage Replacement Rate vs. Maximum Benefit Duration†
Published 2018-08-01“…To this end, I build and calibrate an overlapping generation model which reflects the heterogeneity of the unemployed and the specificity of the unemployment insurance (UI) system in Korea. …”
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1876
Expressibility and trainability of parametrized analog quantum systems for machine learning applications
Published 2020-12-01“…We conclude our work with an example application in generative modeling employing a well studied analog many-body model of a driven Ising spin chain. …”
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1877
Evaluation of Deep Convolutional Generative Adversarial Networks for Data Augmentation of Chest X-ray Images
Published 2020-12-01“…In this study, we performed data augmentation on the Chest X-ray dataset to generate artificial chest X-ray images of the under-represented class through generative modeling techniques such as the Deep Convolutional Generative Adversarial Network (DCGAN). …”
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1878
Machine learning for data integration in human gut microbiome
Published 2022-11-01“…For analysis of such data, machine learning algorithms have shown to be useful for identifying key molecular signatures, discovering potential patient stratifications, and particularly for generating models that can accurately predict phenotypes. …”
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1879
Generating Music with Data: Application of Deep Learning Models for Symbolic Music Composition
Published 2023-04-01“…However, the evaluation of symbolic musical generation models is mostly based on low-level mathematical metrics (e.g., the result of the loss function) due to the inherent difficulty in measuring the musical quality of a given performance due to the subjective nature of music. …”
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1880
MSGeN: Multimodal Selective Generation Network for Grounded Explanations
Published 2023-12-01“…Our extensive experimentation demonstrates that MSGeN surpasses existing multimodal explanation generation models across various metrics, including BLEU, METEOR, ROUGE, CIDEr, SPICE, and Grounding. …”
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Article