Search Results - CCS Concepts: • Computing methodologies → Machine learning algorithms

A Machine Learning Algorithm for Quantitatively Diagnosing Oxidative Stress Risks in Healthy Adult Individuals Based on Health Space Methodology: A Proof-of-Concept Study Using Korean Cross-Sectional Cohort Data by Kim, Youjin, Kim, Yunsoo, Hwang, Jiyoung, van den Broek, Tim J., Oh, Bumjo, Kim, Ji Yeon, Wopereis, Suzan, Bouwman, Jildau, Kwon, Oran

“…” statistical methodology. We then developed a machine learning algorithm for discrimination of oxidative stress status using least absolute shrinkage and selection operator (LASSO…”
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Latent Space Physics: Towards Learning the Temporal Evolution of Fluid Flow by Wiewel, S., Becher, M., Thuerey, N.

“…We propose a method for the data‐driven inference of temporal evolutions of physical functions with deep learning…”
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Llanimation: Llama Driven Gesture Animation by Windle, J, Matthews, I, Taylor, S

“…Co‐speech gesturing is an important modality in conversation, providing context and social cues. In character animation, appropriate and synchronised gestures…”
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Towards a Better Evaluation of 3D CVML Algorithms: Immersive Debugging of a Localization Model by Lin, T., Yuan, J., Miao, K., Katolikyan, T., Walker, I., Cavallo, M.

“…As advancements in robotics, autonomous driving, and spatial computing continue to unfold, a growing number of Computer Vision and Machine Learning (CVML…”
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Learning Metric Fields for Fast Low‐Distortion Mesh Parameterizations by Fargion, G., Weber, O.

“…We present a fast and robust method for computing an injective parameterization with low isometric distortion for disk…”
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Neurosymbolic Models for Computer Graphics by Ritchie, Daniel, Guerrero, Paul, Jones, R. Kenny, Mitra, Niloy J., Schulz, Adriana, Willis, Karl D. D., Wu, Jiajun

“… (via examples, constraints, or objectives), while a search, optimization, or learning algorithm takes care of the details…”
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FlatCAD: Fast Curvature Regularization of Neural SDFs for CAD Models by Yin, Haotian, Plocharski, Aleksander, Wlodarczyk, Michal Jan, Kida, Mikolaj, Musialski, Przemyslaw

“…Neural signed‐distance fields (SDFs) are a versatile backbone for neural geometry representation, but enforcing CAD‐style developability usually requires…”
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A Hybrid Parametrization Method for B‐Spline Curve Interpolation via Supervised Learning by Song, Tianyu, Shen, Tong, Ge, Linlin, Feng, Jieqing

“…B‐spline curve interpolation is a fundamental algorithm in computer‐aided geometric design…”
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In‐the‐wild Material Appearance Editing using Perceptual Attributes by Subias, J. Daniel, Lagunas, M.

“…Intuitively editing the appearance of materials from a single image is a challenging task given the complexity of the interactions between light and matter,…”
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Visual Analytics on Network Forgetting for Task‐Incremental Learning by Li, Ziwei, Xu, Jiayi, Chao, Wei‐Lun, Shen, Han‐Wei

“…Task‐incremental learning (Task‐IL) aims to enable an intelligent agent to continuously accumulate knowledge from new learning tasks without catastrophically forgetting what it has learned in the past…”
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A Survey of Non‐Rigid 3D Registration by Deng, Bailin, Yao, Yuxin, Dyke, Roberto M., Zhang, Juyong

“… In particular, we review different approaches for representing the deformation field, and the methods for computing the desired deformation. Both optimization‐based and learning…”
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Human–machine interaction in building an English reference dataset for natural language processing tasks by Žitko, Branko, Gašpar, Angelina, Bročić, Lucija, Vasić, Daniel, Grubišić, Ani

“…Rich in information and annotated instances, a reference annotated dataset is essential for the training and evaluation of Natural Language Processing (NLP)…”
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Scalable Surface Reconstruction with Delaunay‐Graph Neural Networks by Sulzer, R., Landrieu, L., Marlet, R., Vallet, B.

“…We introduce a novel learning‐based, visibility‐aware, surface reconstruction method for large‐scale, defect‐laden point clouds…”
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HidingGAN: High Capacity Information Hiding with Generative Adversarial Network by Wang, Zihan, Gao, Neng, Wang, Xin, Xiang, Ji, Zha, Daren, Li, Linghui

“… Benefitting from the rapid development of deep neural networks, many steganographic algorithms based on deep learning have been proposed…”
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Linear Time Stable PD Controllers for Physics‐based Character Animation by Yin, Zhiqi, Yin, KangKang

“…) dense matrix factorization based method. In this paper, we propose a linear time algorithm for SPD computation, which is based on Featherstone's forward dynamics formulation for articulated rigid body systems in generalized coordinates [Fea14…”
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A TransISP Based Image Enhancement Method for Visual Disbalance in Low‐light Images by Wu, Jiaqi, Guo, Jing, Jing, Rui, Zhang, Shihao, Tian, Zijian, Chen, Wei, Wang, Zehua

“…Existing image enhancement algorithms often fail to effectively address issues of visual disbalance, such as brightness unevenness and color distortion, in low‐light images…”
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Learning Image Fractals Using Chaotic Differentiable Point Splatting by Djeacoumar, A., Mujkanovic, F., Seidel, H.‐P., Leimkühler, T.

“… We introduce a novel algorithm that optimizes Iterated Function System parameters using a custom fractal generator combined with differentiable point splatting…”
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Semi‐Supervised 3D Shape Recognition via Multimodal Deep Co‐training by Song, Mofei, Liu, Yu, Liu, Xiao Fan

“… With the rapid development of deep learning, various deep models have been introduced and achieved remarkable results…”
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QUESTO: Interactive Construction of Objective Functions for Classification Tasks by Das, Subhajit, Xu, Shenyu, Gleicher, Michael, Chang, Remco, Endert, Alex

“…s. Machine learning algorithms allow for flexible specification of such meta‐information through the design of the objective functions that they solve…”
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PointProNets: Consolidation of Point Clouds with Convolutional Neural Networks by Roveri, Riccardo, Öztireli, A. Cengiz, Pandele, Ioana, Gross, Markus

“… There are numerous algorithms that rely on a variety of assumptions such as local smoothness to tackle this ill‐posed problem…”
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