New Features dCGP-ANNs are added to the available expressions New kernels are available for CGP CGP expressions can be evaluated in parallel backpropagation is implemented in dCGPANNs Bug Fixes Protected division had several issues and is now working as expected The dCGP headers have an improved usability in third party project
DNNs have been finding a growing number of applications including image classification, speech recog...
ABSTRACT: Performance improvements of vlsi parallel systems, using dynamic concatenation of processi...
This release introduces many new features and optimizations. All models can now be solved using the ...
This release come with various important new features on the Python side. Most importantly, kernels,...
This is the largest dcgp release so far, coming after several months of hard work by the development...
Adds dcpg_eval_perf.py and R markdown files for computing and visualizing performance metrics genome...
A small point release to fix the build of the pip packages due to the version number not being updat...
This is a minor release including updates to soem of the third party dependencies we typically build...
Phenotype correction New features Phenotype correction implemented and exposed. Allows for the symb...
Minor Release small bug fixes code sanity initial implementation of a few important, albeit undocum...
Artifact for accepted OSDI'23 paper, Yuke Wang, et al. MGG: Accelerating Graph Neural Networks with ...
<p>Performance comparison of DCA against other algorithms on dynamic DIP network.</p
In this release we did introduce a few bug fixes #59 #57 thanks to @hejung, but mostly we reworked t...
In the past two years, various graph convolution neural networks (GCNs) accelerators have emerged, e...
New A new UDA is introduced to solve symbolic regression problems. Its called moes (Multi-Objecti...
DNNs have been finding a growing number of applications including image classification, speech recog...
ABSTRACT: Performance improvements of vlsi parallel systems, using dynamic concatenation of processi...
This release introduces many new features and optimizations. All models can now be solved using the ...
This release come with various important new features on the Python side. Most importantly, kernels,...
This is the largest dcgp release so far, coming after several months of hard work by the development...
Adds dcpg_eval_perf.py and R markdown files for computing and visualizing performance metrics genome...
A small point release to fix the build of the pip packages due to the version number not being updat...
This is a minor release including updates to soem of the third party dependencies we typically build...
Phenotype correction New features Phenotype correction implemented and exposed. Allows for the symb...
Minor Release small bug fixes code sanity initial implementation of a few important, albeit undocum...
Artifact for accepted OSDI'23 paper, Yuke Wang, et al. MGG: Accelerating Graph Neural Networks with ...
<p>Performance comparison of DCA against other algorithms on dynamic DIP network.</p
In this release we did introduce a few bug fixes #59 #57 thanks to @hejung, but mostly we reworked t...
In the past two years, various graph convolution neural networks (GCNs) accelerators have emerged, e...
New A new UDA is introduced to solve symbolic regression problems. Its called moes (Multi-Objecti...
DNNs have been finding a growing number of applications including image classification, speech recog...
ABSTRACT: Performance improvements of vlsi parallel systems, using dynamic concatenation of processi...
This release introduces many new features and optimizations. All models can now be solved using the ...
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