vix.ing · top · new · best · stats · spec

Hodas, Nathan O.

  1. SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties
    2017/12/05 by Garrett B. Goh, Nathan O. Hodas, Goh, Garrett B. +5 · 4 citations
    Chemistry · Computer Science · Materials Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computational Drug Discovery Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Various Chemistry Research Topics
  2. Friendship Paradox Redux: Your Friends Are More Interesting Than You
    2013/04/11 by Hodas, Nathan O., Kooti, Farshad, Lerman, Kristina · 3 citations
    #Adaptation and Self-Organizing Systems (nlin.AO) #Applications (stat.AP) #Computers and Society (cs.CY) #FOS: Computer and information sciences #FOS: Physical sciences #G.2.2 #G.3 #J.4 #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)
  3. Network Weirdness: Exploring the Origins of Network Paradoxes
    2014/03/27 by Kooti, Farshad, Hodas, Nathan O., Lerman, Kristina · 3 citations
    #Computers and Society (cs.CY) #FOS: Computer and information sciences #FOS: Physical sciences #G.2.2 #G.3 #J.4 #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)
  4. Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models
    2017/06/20 by Goh, Garrett B., Siegel, Charles, Vishnu, Abhinav +2 · 3 citations
    #Artificial Intelligence (cs.AI) #Computational Engineering #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Finance #Machine Learning (cs.LG) #Machine Learning (stat.ML) #and Science (cs.CE)
  5. Deep Learning for Computational Chemistry
    2017/01/17 by Goh, Garrett B., Hodas, Nathan O., Vishnu, Abhinav · 2 citations
    #Artificial Intelligence (cs.AI) #Chemical Physics (physics.chem-ph) #Computational Engineering #FOS: Computer and information sciences #FOS: Physical sciences #Finance #Machine Learning (cs.LG) #Machine Learning (stat.ML) #and Science (cs.CE)
  6. A Koopman Operator Approach for Computing and Balancing Gramians for Discrete Time Nonlinear Systems
    2017/09/25 by Yeung, Enoch, Liu, Zhiyuan, Hodas, Nathan O. · 2 citations
    #FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering
  7. Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction
    2017/12/07 by Garrett B. Goh, Charles Siegel, Goh, Garrett B. +5 · 2 citations
    Computer Science · Materials Science · Chemistry · #Computational Drug Discovery Methods #Machine Learning in Materials Science #Analytical Chemistry and Chromatography
  8. Few-Shot Learning with Metric-Agnostic Conditional Embeddings
    2018/02/12 by Hilliard, Nathan, Phillips, Lawrence, Howland, Scott +3 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  9. Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples
    2019/05/21 by Colby, Sean M., Nuñez, Jamie R., Hodas, Nathan O. +2 · 1 citation
    #Biomolecules (q-bio.BM) #FOS: Biological sciences