TensorLayer: A Versatile Library for Efficient Deep Learning Development
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Abstract (arXiv)
Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others. Developing a deep learning system is arduous and complex, as it involves constructing neural network architectures, managing training/trained models, tuning optimization process, preprocessing and organizing data, etc. TensorLayer is a versatile Python library that aims at helping researchers and engineers efficiently develop deep learning systems. It offers rich abstractions for neural networks, model and data management, and parallel workflow mechanism. While boosting efficiency, TensorLayer maintains both performance and scalability. TensorLayer was released in September 2016 on GitHub, and has helped people from academia and industry develop real-world applications of deep learning.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jul 2017.
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Citing papers per year: 2021: 4; 2022: 0; 2023: 1; 2024: 1.
6 papers.
- 2021FinRL: Deep Reinforcement Learning Framework to Automate Trading in Quantitative Financecited by 57
- 2021Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesiscited by 20
- 2023Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-artcited by 14
- 2021Fast and Flexible Human Pose Estimation with HyperPosecited by 5
- 2021A Survey and Analysis on Automated Glioma Brain Tumor Segmentation and Overall Patient Survival Predictioncited by 1
- 2024Power-Efficient Image Storage: Leveraging Super Resolution Generative Adversarial Network for Sustainable Compression and Reduced Carbon Footprintcited by 0
- 2024Power-Efficient Image Storage: Leveraging Super Resolution Generative Adversarial Network for Sustainable Compression and Reduced Carbon Footprint6 Apr 2024
- 2023Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art30 Aug 2023
- 2021FinRL: Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance7 Nov 2021
- 2021Fast and Flexible Human Pose Estimation with HyperPose26 Aug 2021
- 2021Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis22 Jun 2021
- 2021A Survey and Analysis on Automated Glioma Brain Tumor Segmentation and Overall Patient Survival Prediction26 Jan 2021