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41-50 trong số 74 kết quả
Learning from the past [electronic resource] : Are catalyst design principles transferrable between hydrodesulfurization...
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2018
Bộ sưu tập: Metadata
ddc:  621.49
 
DOE SBIR Phase-1 Report on Hybrid CPU-GPU Parallel Development of the Eulerian-Lagrangian Barracuda Multiphase Program [...
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2011
Bộ sưu tập: Metadata
ddc:  622.27
 
High-throughput cancer hypothesis testing with an integrated PhysiCell-EMEWS workflow [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2018
Bộ sưu tập: Metadata
ddc:  611.39
 
Enhancing disease surveillance with novel data streams [electronic resource] : challenges and opportunities
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2015
Bộ sưu tập: Metadata
ddc:  545
 
Deep Learning Approaches to Surrogates for Solving the Diffusion Equation for Mechanistic Real-World Simulations [electr...
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2021
Bộ sưu tập: Metadata
ddc:  610.28
 
Learning curves for drug response prediction in cancer cell lines [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2021
Bộ sưu tập: Metadata
ddc:  577.3
 
Computer-aided classification of suspicious pigmented lesions using wide-field images [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2020
Bộ sưu tập: Metadata
ddc:  621.36
 
Computer Modeling Illuminates Degradation Pathways of Cations in Alkaline Membrane Fuel Cells (Fact Sheet) [electronic r...
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2012
Bộ sưu tập: Metadata
ddc:  621.311
 
Unified rational protein engineering with sequence-based deep representation learning [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2019
Bộ sưu tập: Metadata
ddc:  572.6
 
Classifying Cancer Pathology Reports with Hierarchical Self-Attention Networks [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2019
Bộ sưu tập: Metadata
ddc:  616.99
 

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