Pinned Repositories
AsyncFedGAN
An Efficient and Staleness-aware Asynchronous Federated Learning Framework for Generative Adversarial Networks
AsyncFedInv-Asynchronous-Federated-learning-for-Seismic-Inversion
Conditional-GraphGANFed
DAC_YoungFellows
DAC-YF Files
Federated-GAN-for-Drug-Discovery
Graph-Neural-Networks
Fast exploration for best GNN architectures and novel RL controller to train and validate the network on well known datasets (Cora, Citeseer, Pubmed and PPI)
GraphGANFed
Design of a molecular generative framework that integrates federated learning into generative adversarial network and graph convolutional network to generate highly novel and diverse molecular samples which are evaluated using benchmark drug evaluation metrics such as validity, uniqueness, diversity, novelty, drug-likeliness and LogP scores.
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Seismic-Inversion-on-edge-devices-
v70
Proceedings of ICML 2017
danielmanu93's Repositories
danielmanu93/Graph-Neural-Networks
Fast exploration for best GNN architectures and novel RL controller to train and validate the network on well known datasets (Cora, Citeseer, Pubmed and PPI)
danielmanu93/AsyncFedGAN
An Efficient and Staleness-aware Asynchronous Federated Learning Framework for Generative Adversarial Networks
danielmanu93/AsyncFedInv-Asynchronous-Federated-learning-for-Seismic-Inversion
danielmanu93/Conditional-GraphGANFed
danielmanu93/DAC_YoungFellows
DAC-YF Files
danielmanu93/Federated-GAN-for-Drug-Discovery
danielmanu93/GraphGANFed
Design of a molecular generative framework that integrates federated learning into generative adversarial network and graph convolutional network to generate highly novel and diverse molecular samples which are evaluated using benchmark drug evaluation metrics such as validity, uniqueness, diversity, novelty, drug-likeliness and LogP scores.
danielmanu93/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
danielmanu93/Seismic-Inversion-on-edge-devices-
danielmanu93/v70
Proceedings of ICML 2017