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We tackle the challenge of feature embedding for the purposes of improving the click-through rate prediction process. We select three models: logistic regression, factorization machines and deep factorization machines, as our baselines and…

Machine Learning · Computer Science 2022-09-21 Samo Pahor , Davorin Kopič , Jure Demšar

The predictive accuracy of Machine Learning (ML) models of molecular properties depends on the choice of the molecular representation. Based on the postulates of quantum mechanics, we introduce a hierarchy of representations which meet…

Chemical Physics · Physics 2016-11-23 Bing Huang , O. Anatole von Lilienfeld

Few-shot learning is a promising approach to molecular property prediction as supervised data is often very limited. However, many important molecular properties depend on complex molecular characteristics -- such as the various 3D…

Machine Learning · Computer Science 2023-10-10 Christopher Fifty , Joseph M. Paggi , Ehsan Amid , Jure Leskovec , Ron Dror

Microfluidic devices offer numerous advantages in medical applications, including the capture of single cells in microwell-based platforms for genomic analysis. As the cost of sequencing decreases, the demand for high-throughput single-cell…

Computational Engineering, Finance, and Science · Computer Science 2024-09-13 Xueying Zhao , Yan Chen , Yuefu Jiang , Amie Radenbaugh , Jamie Moskwa , Devon Jensen

There are many methods proposed for inferring parameters of the Ising model from given data, that is a set of configurations generated according to the model itself. However little attention has been paid until now to the data, e.g. how the…

Statistical Mechanics · Physics 2016-09-01 Aurélien Decelle , Federico Ricci-Tersenghi , Pan Zhang

It is important to develop sustainable processes in materials science and manufacturing that are environmentally friendly. AI can play a significant role in decision support here as evident from our earlier research leading to tools…

Artificial Intelligence · Computer Science 2023-03-27 Aparna S. Varde , Jianyu Liang

Many analyses in particle and nuclear physics use simulations to infer fundamental, effective, or phenomenological parameters of the underlying physics models. When the inference is performed with unfolded cross sections, the observables…

Data Analysis, Statistics and Probability · Physics 2024-09-19 Owen Long , Benjamin Nachman

Data imbalance is common in production data, where controlled production settings require data to fall within a narrow range of variation and data are collected with quality assessment in mind, rather than data analytic insights. This…

Machine Learning · Statistics 2021-12-17 Rune D. Kjærsgaard , Manja G. Grønberg , Line K. H. Clemmensen

In ultrasound tomography, the speed of sound inside an object is estimated based on acoustic measurements carried out by sensors surrounding the object. An accurate forward model is a prominent factor for high-quality image reconstruction,…

Image and Video Processing · Electrical Eng. & Systems 2021-11-24 Janne Koponen , Timo Lähivaara , Jari Kaipio , Marko Vauhkonen

We present a neural network for predicting purchasing intent in an Ecommerce setting. Our main contribution is to address the significant investment in feature engineering that is usually associated with state-of-the-art methods such as…

Machine Learning · Computer Science 2018-07-24 Humphrey Sheil , Omer Rana , Ronan Reilly

In object detection with deep neural networks, the box-wise objectness score tends to be overconfident, sometimes even indicating high confidence in presence of inaccurate predictions. Hence, the reliability of the prediction and therefore…

Computer Vision and Pattern Recognition · Computer Science 2020-10-07 Marius Schubert , Karsten Kahl , Matthias Rottmann

We apply recent advances in machine learning and computer vision to a central problem in materials informatics: The statistical representation of microstructural images. We use activations in a pre-trained convolutional neural network to…

Computational Physics · Physics 2018-12-04 Nicholas Lubbers , Turab Lookman , Kipton Barros

Quantum computers can be considered as a natural means for performing machine learning tasks for inherently quantum labeled data. Many quantum machine learning techniques have been developed for solving classification problems, such as…

Quantum Physics · Physics 2025-01-24 Andrey Kardashin , Yerassyl Balkybek , Vladimir V. Palyulin , Konstantin Antipin

Frequency estimation from measurements corrupted by noise is a fundamental challenge across numerous engineering and scientific fields. Among the pivotal factors shaping the resolution capacity of any frequency estimation technique are…

Signal Processing · Electrical Eng. & Systems 2024-09-23 Sampath Kumar Dondapati , Omkar Nitsure , Satish Mulleti

The semiconductor industry is one of the most technology-evolving and capital-intensive market sectors. Effective inspection and metrology are necessary to improve product yield, increase product quality and reduce costs. In recent years,…

Machine Learning · Computer Science 2023-10-12 Angzhi Fan , Yu Huang , Fei Xu , Sthitie Bom

Revealing and analyzing the various properties of materials is an essential and critical issue in the development of materials, including batteries, semiconductors, catalysts, and pharmaceuticals. Traditionally, these properties have been…

Machine Learning · Computer Science 2023-08-21 Limin Wang , Masatoshi Hanai , Toyotaro Suzumura , Shun Takashige , Kenjiro Taura

We investigated the accelerated prediction of the thermal conductivity of materials through end- to-end structure-based approaches employing machine learning methods. Due to the non-availability of high-quality thermal conductivity data, we…

Materials Science · Physics 2023-11-07 Yagyank Srivastava , Ankit Jain

The application of machine learning to physics problems is widely found in the scientific literature. Both regression and classification problems are addressed by a large array of techniques that involve learning algorithms. Unfortunately,…

Machine Learning · Computer Science 2022-10-03 Umberto Michelucci , Francesca Venturini

Injection moulding is an increasingly automated industrial process, particularly when used for the production of high-value precision components such as polymeric medical devices. In such applications, achieving stringent product quality…

Systems and Control · Electrical Eng. & Systems 2022-02-04 Mandana Kariminejad , David Tormey , Saif Huq , Jim Morrison , Marion McAfee

The design of high-entropy alloys (HEA) with desired properties is challenging due to their large compositional space. While various machine learning (ML) models can predict specific HEA solid-solution phases (SS), predicting high-entropy…

Materials Science · Physics 2023-06-27 Jie Qi , Diego Ibarra Hoyos , S. Joseph Poon
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