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61

TorchBraid: High-Performance Layer-Parallel Training of Deep Neural Networks with MPI and GPU Acceleration.
CYR, ERIC C. ; HAHNE, JENS ; MOORE, NICHOLAS S. ; et al.
ACM Transactions on Mathematical Software; Sep2025, Vol. 51 Issue 3, p1-30, 30p

PARALLEL processing GRAPHICS processing unit... ARTIFICIAL neural networ... PARALLEL programming IMAGE recognition (Compu... AUTOMATIC differentiatio...
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62

What do Programmers Discuss about Deep Learning Frameworks.
Han, Junxiao ; Shihab, Emad ; Wan, Zhiyuan ; et al.
Empirical Software Engineering; Jul2020, Vol. 25 Issue 4, p2694-2747, 54p

DEEP learning COMPUTER software develo... COMPUTER programmers PROGRAMMING languages WORKFLOW management SOFTWARE engineering
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63

Efficient and Stable Coupling of the SuperdropNet Deep Learning-based Cloud Microphysics (v0.1.0) to the ICON Climate and Weather Model (v2.6.5).
Arnold, Caroline ; Sharma, Shivani ; Weigel, Tobias ; et al.
EGUsphere; 11/15/2023, p1-17, 17p

MACHINE learning ATMOSPHERIC models MICROPHYSICS CLOUD droplets SOFTWARE development too... EMULATION software …
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64

TorchDA: A Python package for performing data assimilation with deep learning forward and transformation functions.
Cheng, Sibo ; Min, Jinyang ; Liu, Che ; et al.
Computer Physics Communications. Jan2025, Vol. 306, pN.PAG-N.PAG. 1p.

ARTIFICIAL neural networ... PYTHON programming langu... DATA assimilation WATER depth KALMAN filtering PROGRAMMING languages …
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65

Studies on Environmental Impact and Energy Efficiency of Artificial Intelligence and Machine Learning.
Damkaci, Yavuz E.
International Journal of High School Research; Aug2023, Vol. 5 Issue 4, p126-133, 8p

ENVIRONMENTAL impact ana... ARTIFICIAL intelligence MACHINE learning ENERGY consumption DEEP learning JAVA programming languag...
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66

DeepOnto: A Python package for ontology engineering with deep learning: A Python Package for Ontology Engineering with Deep Learning
He, Y ; Chen, J ; Dong, H ; et al.
He, Y, Chen, J, Dong, H, Horrocks, I, Allocca, C, Kim, T & Sapkota, B 2024, 'DeepOnto : A Python Package for Ontology Engineering with Deep Learning', Semantic Web, vol. 15, no. 5, pp. 1991-2004. https://doi.org/10.3233/SW-243

FOS: Computer and inform... Computer Science - Machi... Computer Science - Logic... Computer Science - Compu... Language Mode Ontology …
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67

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68

Comprehensive Review and Comparative Analysis of Keras for Deep Learning Applications: A Survey on Face Detection Using Convolutional Neural Networks
Noor Abdalkareem Lafta ; Zainab Ali Abbood Abbood
International Journal of Religion. 5:1203-1213

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69

Slapo: A Schedule Language for Progressive Optimization of Large Deep Learning Model Training
Hongzheng Chen ; Cody Hao Yu ; Shuai Zheng ; et al.
Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2. :1095-1111

FOS: Computer and inform... Computer Science - Machi... 0202 electrical engineer... 02 engineering and techn... 01 natural sciences 0105 earth and related e... …
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70

Improving the performance of a deep learning framework on high-performance computing (HPC) systems
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial ; Pérez Magrané, Ramon ; Morcego Seix, Bernardo ; et al.

E-Ressource
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71

DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science
Li, Mufei ; Zhou, Jinjing ; Hu, Jiajing ; et al.
ACS Omega. 6(41):27233-27238

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72

RoseNNa: A performant, portable library for neural network inference with application to computational fluid dynamics
Bati, Ajay ; Bryngelson, Spencer H.
In Computer Physics Communications March 2024 296

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73

Super-resolution of satellite images: Feasibility of deep learning techniques.
Akimova, Elena N. ; Deikov, Artem A.
AIP Conference Proceedings; 2020, Vol. 2293 Issue 1, p140002-1-140002-4, 4p

HIGH resolution imaging CONVOLUTIONAL neural net... REMOTE-sensing images PYTHON programming langu... INTERPOLATION algorithms DEEP learning …
Konferenz
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74

DIVA-DAF: A Deep Learning Framework for Historical Document Image Analysis
Vögtlin, Lars ; Scius-Bertrand, Anna ; Maergner, Paul ; et al.

Computer Science - Compu...
Report
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75

Deep Declarative Networks.
Gould, Stephen ; Hartley, Richard ; Campbell, Dylan
IEEE Transactions on Pattern Analysis & Machine Intelligence; Aug2022, Vol. 44 Issue 8, p3988-4004, 17p

DEEP learning ELECTRONIC data processi... IMPLICIT functions MATHEMATICAL optimizatio... PROGRAMMING languages POINT cloud
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78

DiffBreed: automatic differentiation enables efficient gradient-based optimization of breeding strategies Open Access.
Hamazaki, Kosuke ; Iwata, Hiroyoshi ; Tsuda, Koji
Bioinformatics. Nov2025, Vol. 41 Issue 11, p1-10. 10p.

AUTOMATIC differentiatio... ANIMAL breeding BIOLOGICAL models
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79

CalcGraph: taming the high costs of deep learning using models
Lorentz, Joe ; Hartmann, Thomas ; Moawad, Assaad ; et al.

E-Ressource
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80

Pyro: Deep Universal Probabilistic Programming.
Bingham, Eli ; Chen, Jonathan P. ; Jankowiak, Martin ; et al.
Journal of Machine Learning Research. 2019, Vol. 20 Issue 2-29, p1-6. 6p.

PROGRAMMING languages PROBABILITY theory STOCHASTIC analysis INFERENTIAL statistics DEEP learning
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