Results 151 to 160 of about 151,967 (341)

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu, Pan Zhang, Shangqian Wu, Hao Sun, Minwei Li, Sophia Tsoka, Zizhang Sheng, Lei Deng   +7 more
wiley   +1 more source

The Role of Hyperparameters in Predictive Multiplicity

CoRR
16 pages, 4 ...
Mustafa Cavus, Katarzyna Woznica, Przemyslaw Biecek   +2 more
openaire   +2 more sources

Machine Learning for Green Solvents: Assessment, Selection and Substitution

Advanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta, Janhavi Nistane, Abhishek Sose, Harikrishna Sahu, Rampi Ramprasad   +4 more
wiley   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

A Photosynthetic Rate Prediction Model for Cucumber Based on a Machine Learning Algorithm and Multi-Factor Environmental Analysis

Horticulturae
Plant photosynthetic rate prediction models have the potential to enhance production efficiency and advance intelligent control in protected agriculture.
Yanxiu Miao, Liyuan Liu, Miaoyu Wang, Zhihao Zeng, Jun Zhang, Yongsan Cheng, Bin Li   +6 more
doaj   +1 more source

Tutorium "Hyperparameter Optimization"

, 2019
Part I: Theory - Train / development / test sets - Regularization techniques (dropout, L1/L2-regularization) - Optimization algorithms - Batch normalization - Grid search vs. random search vs. Bayesian optimization vs.
Rüttgers, Alexander, Debus, Charlotte
core  

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

Enhancing Short-Term Load Forecasting Using Hyperparameter-Optimized Deep Learning Approaches

Energies
The reliability and efficiency of power system operations, especially in smart grid scenarios, depend on accurate load demand forecasting. Electrical load forecasting is crucial for power system design, fault protection and diversification as it reduces ...
Nazmun Nahar Karima, Shameem Ahmad, Amirul Islam, A.S. Nazmul Huda, Lilik Jamilatul Awalin, Syahirah Abd Halim, Hazlie Mokhlis, Mohd Syukri Ali, Syahril Mubarok   +8 more
doaj   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

EV-Planner: a machine learning approach to electric vehicle charging infrastructure planning

Frontiers in Artificial Intelligence
Electric Vehicles (EVs) offer pathways to lower emissions and increased energy efficiency. However, a broad and equitable adoption of electric vehicles can only be realized with well-planned growth in public charging infrastructure. We propose EV-Planner,
Bharath Anand, Ananth Grama
doaj   +1 more source