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Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction.

, , , and . KDD, page 302-310. ACM, (2018)

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Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction, , , and . (2017)cite arxiv:1712.02734Comment: Submitted to SIGKDD 2018.SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties, , , and . (2017)cite arxiv:1712.02034Comment: Submitted to SIGKDD 2018.What does fault tolerant deep learning need from MPI?, , , and . EuroMPI/USA, page 13:1-13:11. ACM, (2017)Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction., , , and . KDD, page 302-310. ACM, (2018)How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions?, , , , and . (2017)cite arxiv:1710.02238Comment: In Proceedings of 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).GossipGraD: Scalable Deep Learning using Gossip Communication based Asynchronous Gradient Descent, , , , and . (2018)cite arxiv:1803.05880Comment: 13 pages, 17 figures.User-transparent Distributed TensorFlow., , , and . CoRR, (2017)Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing., , , , and . Future Gener. Comput. Syst., (2020)Adaptive neuron apoptosis for accelerating deep learning on large scale systems., , and . IEEE BigData, page 753-762. IEEE Computer Society, (2016)A Learning Framework for Control-Oriented Modeling of Buildings., , , , and . ICMLA, page 473-478. IEEE, (2017)