Statistics for topic neural-architecture-search
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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...
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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...
Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
A curated list of automated machine learning papers, articles, tutorials, slides and projects
This is a list of interesting papers and projects about TinyML.
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.
Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.
A curated list of awesome resources combining Transformers with Neural Architecture Search
A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)
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
Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.
This is a list of interesting papers and projects about TinyML.
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.
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.
