Changelog Description Welcome to v3.1.0 release. In this release, we implemented the initial parts for holding graph-related searches, which will support Neural Architecture Search (NAS) in the feature. Additionally, we have added the first algorithm for calculating the Pareto frontier of pre-defined points (Non-Dominated Sorting). Includes (or changes) core optimizers space
Much improved surface generation algorithm that provides for orthogonality constraints. Transition s...
Existing neural architecture search (NAS) methods often operate in discrete or continuous spaces dir...
Deep learning has made substantial breakthroughs in many fields due to its powerful automatic repres...
Changelog Description Welcome to v3.1.0 release. In this release, we implemented the initial parts f...
Changelog Description Welcome to v3.0.1 release. In this release, we have added a bunch of meta-heur...
Changelog Description Welcome to v3.1.3 release. In this release, we added two new optimizers. Inclu...
Changelog Description Welcome to v3.0.0 release. In this release, we have revamped the whole libra...
Changelog Description Welcome to v3.0.2 release. In this release, we implemented the remaining meta-...
Changelog Description Welcome to v2.1.3 release. In this release, we have added the following opti...
Changelog Description Welcome to v3.1.1 release. In this release, we added pre-commit hooks and anno...
Automating the research for the best neural network model is a task that has gained more and more re...
Neural Architecture Search (NAS) automates and prospers the design of neural networks. Estimator-bas...
POPNASv3 is a neural architecture search algorithm that employs a sequential model-based optimizatio...
Lots of effort in neural architecture search (NAS) research has been dedicated to algorithmic develo...
Highlights This release is the result of over 2 months of work with over 16 pull requests by 4 cont...
Much improved surface generation algorithm that provides for orthogonality constraints. Transition s...
Existing neural architecture search (NAS) methods often operate in discrete or continuous spaces dir...
Deep learning has made substantial breakthroughs in many fields due to its powerful automatic repres...
Changelog Description Welcome to v3.1.0 release. In this release, we implemented the initial parts f...
Changelog Description Welcome to v3.0.1 release. In this release, we have added a bunch of meta-heur...
Changelog Description Welcome to v3.1.3 release. In this release, we added two new optimizers. Inclu...
Changelog Description Welcome to v3.0.0 release. In this release, we have revamped the whole libra...
Changelog Description Welcome to v3.0.2 release. In this release, we implemented the remaining meta-...
Changelog Description Welcome to v2.1.3 release. In this release, we have added the following opti...
Changelog Description Welcome to v3.1.1 release. In this release, we added pre-commit hooks and anno...
Automating the research for the best neural network model is a task that has gained more and more re...
Neural Architecture Search (NAS) automates and prospers the design of neural networks. Estimator-bas...
POPNASv3 is a neural architecture search algorithm that employs a sequential model-based optimizatio...
Lots of effort in neural architecture search (NAS) research has been dedicated to algorithmic develo...
Highlights This release is the result of over 2 months of work with over 16 pull requests by 4 cont...
Much improved surface generation algorithm that provides for orthogonality constraints. Transition s...
Existing neural architecture search (NAS) methods often operate in discrete or continuous spaces dir...
Deep learning has made substantial breakthroughs in many fields due to its powerful automatic repres...
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