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High-order neural networks and kernel methods for peptide-MHC binding prediction.

, , , and . Bioinform., 31 (22): 3600-3607 (2015)

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Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent., , , and . CoRR, (2016)Adaptive Feature Abstraction for Translating Video to Language., , , and . ICLR (Workshop), OpenReview.net, (2017)Exemplar-centered Supervised Shallow Parametric Data Embedding., , and . IJCAI, page 2479-2485. ijcai.org, (2017)DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays., , , , , , , and . Bioinform., 37 (Supplement): 280-288 (2021)A Deep Non-linear Feature Mapping for Large-Margin kNN Classification., , , , and . ICDM, page 357-366. IEEE Computer Society, (2009)T-Cell Receptor-Peptide Interaction Prediction with Physical Model Augmented Pseudo-Labeling., , and . KDD, page 3090-3097. ACM, (2022)Attribute-Centric Compositional Text-to-Image Generation., , , , and . CoRR, (2023)S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation., , , and . CVPR, page 6537-6546. Computer Vision Foundation / IEEE, (2020)Hopper: Multi-hop Transformer for Spatiotemporal Reasoning., , , , , , and . ICLR, OpenReview.net, (2021)High-order neural networks and kernel methods for peptide-MHC binding prediction., , , and . Bioinform., 31 (22): 3600-3607 (2015)