awesome-autodl
github.com/d-x-y/awesome-autodl ↗Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
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2021 Venues2020 Venues2019 Venues2018 Venues2017 VenuesPrevious VenuesarXiv
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2018 Venues
- Accelerating Neural Architecture Search using Performance Prediction
ICLR-W
- A Flexible Approach to Automated RNN Architecture Generation
ICLR
- Differentiable Neural Network Architecture Search
ICLR-W
- Efficient Architecture Search by Network Transformation
AAAI
- Hierarchical Representations for Efficient Architecture Search
ICLR
- Learning Transferable Architectures for Scalable Image Recognition
CVPR
arXiv
- A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions
ACM Computing Surveys
- A Survey on Neural Architecture Search
arXiv
- Automated Machine Learning
Springer Book
- Automated Machine Learning on Graphs: A Survey
ICLR-W
- AutoML: A Survey of the State-of-the-Art
arXiv
- AutonoML: Towards an Integrated Framework for Autonomous Machine Learning
arXiv
2020 Venues
- AdversarialNAS: Adversarial Neural Architecture Search for GANs
CVPR
- Angle-based Search Space Shrinking for Neural Architecture Search
ECCV
- Anti-Bandit Neural Architecture Search for Model Defense
ECCV
- APQ: Joint Search for Network Architecture, Pruning and Quantization Policy
CVPR
- Are Labels Necessary for Neural Architecture Search?
ECCV
- A Semi-Supervised Assessor of Neural Architectures
CVPR
2019 Venues
- A Neurobiological Evaluation Metric for Neural Network Model Search
CVPR
- Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
CVPR
- AutoDispNet: Improving Disparity Estimation With AutoML
ICCV
- AutoGAN: Neural Architecture Search for Generative Adversarial Networks
ICCV
- ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation
CVPR
- Continual and Multi-Task Architecture Search
ACL
2021 Venues
- AutoFormer: Searching Transformers for Visual Recognition
ICCV
- AutoHAS: Differentiable Hyper-parameter and Architecture Search
ICLR-W
- CATE: Computation-aware Neural Architecture Encoding with Transformers
ICML
- DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
ICLR
- DrNAS: Dirichlet Neural Architecture Search
ICLR
- Evolving Reinforcement Learning Algorithms
ICLR
2017 Venues
- Designing Neural Network Architectures using Reinforcement Learning
ICLR
- Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
ICLR
- Hyperparameter Optimization: A Spectral Approach
NeurIPS-W
- Learning Curve Prediction with Bayesian Neural Networks
ICLR
- Neural Architecture Search with Reinforcement Learning
ICLR
- Neural Optimizer Search with Reinforcement Learning
ICML
Showing a sample of 182 resources. View the full list on GitHub →