Results 221 to 230 of about 218,805 (280)

Don't Stop Me Now, `Cause I'm Having a Good Time Screening: Evaluation of Stopping Methods for Safe Use of Priority Screening in Systematic Reviews. [PDF]

Cochrane Evid Synth Methods
Repke T, Tinsdeall F, Danilenko D, Graziosi S, Müller-Hansen F, Schmidt L, Thomas J, van Valkenhoef G.   +7 more
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Impact of decoding strategies on GPU energy usage in large language model text generation. [PDF]

Sci Rep
Nik A, Riegler MA, Halvorsen P.
europepmc   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Unsupervised learning of spatially varying regularization for diffeomorphic image registration. [PDF]

Med Image Anal
Chen J, Wei S, Liu Y, Bian Z, He Y, Carass A, Bai H, Du Y.   +7 more
europepmc   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Application of XGBoost and Random Forest algorithms for body weight prediction in Blackbelly sheep using biometric measurements. [PDF]

BMC Vet Res
Delgado MÁG, Tırınk C, Parra-Cortés RI, Martínez IV, Gomez-Vazquez A, Cruz-Hernandez A, Camacho-Pérez E, Dzib-Cauich DA, Önder H, Şen U, Chekirov K, Aksoy Y, Çelik HT, Odu O, Chay-Canul AJ.   +14 more
europepmc   +1 more source

Exploiting the Kumaraswamy distribution in a reinforcement learning context. [PDF]

Front Robot AI
Picchi D, Brell-Çokcan S.
europepmc   +1 more source

Prediction of Impact Resistance of Nano-SiO₂ and Hybrid Fiber Modified Geopolymer Gel Concrete in Marine Wet-Thermal and Chloride Salt Environment. [PDF]

Gels
Lai C, Zhang P, Dai X, Zheng Y.
europepmc   +1 more source

Enhanced medical image segmentation using optimized bidirectional LSTM and dolphin partner optimizer. [PDF]

PLoS One
Alhassan AM, Altmami NI.
europepmc   +1 more source