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Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data.

, , , and . J. Cheminformatics, 9 (1): 42:1-42:13 (2017)

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Interactions Modeling in Multi-Task Multi-View Learning with Consistent Task Diversity., and . CIKM, page 853-861. ACM, (2018)Chemical Compound Classification with Automatically Mined Structure Patterns., , and . APBC, volume 6 of Advances in Bioinformatics and Computational Biology, page 39-48. Imperial College Press, (2008)An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity., , and . CoRR, (2019)Ultrafast Photorealistic Style Transfer via Neural Architecture Search., , , and . CoRR, (2019)MP2SDA: Multi-Party Parallelized Sparse Discriminant Learning., , , , and . ACM Trans. Knowl. Discov. Data, 14 (3): 26:1-26:22 (2020)Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: I. Method development., , , , , and . J. Comput. Aided Mol. Des., 23 (11): 773-784 (2009)Learning Causal Structures Based on Divide and Conquer., , , , , , and . IEEE Trans. Cybern., 52 (5): 3232-3243 (2022)NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks., , , , , and . CoRR, (2019)Temporal Output Discrepancy for Loss Estimation-based Active Learning., , , , , and . CoRR, (2022)Deep cycle autoencoder for unsupervised domain adaptation with generative adversarial networks., , , and . IET Comput. Vis., 13 (7): 659-665 (2019)