Statistics for topic neural-architecture-search
RepositoryStats tracks 595,856 Github repositories, of these 95 are tagged with the neural-architecture-search topic. The most common primary language for repositories using this topic is Python (76).
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An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A curated list of automated machine learning papers, articles, tutorials, slides and projects
[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang
Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang
A curated list of automated machine learning papers, articles, tutorials, slides and projects
Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A curated list of automated machine learning papers, articles, tutorials, slides and projects
This is a list of interesting papers and projects about TinyML.
Differentiable architecture search for convolutional and recurrent networks
Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
This is a list of interesting papers and projects about TinyML.
NASLib is a Neural Architecture Search (NAS) library for facilitating NAS research for the community by providing interfaces to several state-of-the-art NAS search spaces and optimizers.
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256K...
[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
This is a list of interesting papers and projects about TinyML.
Evolutionary Neural Architecture Search on Transformers for RUL Prediction
Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
This is a list of interesting papers and projects about TinyML.
Official PyTorch implementation of "DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models" (ICLR 2024)
[ISPRS 2024] LoveNAS: Towards Multi-Scene Land-Cover Mapping via Hierarchical Searching Adaptive Network
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
This is a list of interesting papers and projects about TinyML.
A curated list of automated machine learning papers, articles, tutorials, slides and projects
[ISPRS 2024] LoveNAS: Towards Multi-Scene Land-Cover Mapping via Hierarchical Searching Adaptive Network
Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.
Evolutionary Neural Architecture Search on Transformers for RUL Prediction
This is a collection of our research on efficient AI, covering hardware-aware NAS and model compression.
Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.