Convolutional neural network architectures for predicting DNA–protein binding H Zeng, MD Edwards, G Liu, DK Gifford Bioinformatics 32 (12), i121-i127, 2016 | 533 | 2016 |
Antibody Complementarity Determining Region Design Using High-Capacity Machine Learning G Liu, H Zeng, J Mueller, B Carter, Z Wang, J Schilz, G Horny, ... Bioinformatics, 682880, 2019 | 143 | 2019 |
Computationally optimized SARS-CoV-2 MHC class I and II vaccine formulations predicted to target human haplotype distributions G Liu, B Carter, T Bricken, S Jain, M Viard, M Carrington, DK Gifford Cell systems 11 (2), 131-144. e6, 2020 | 65 | 2020 |
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles G Liu, S Jain, J Mueller, D Gifford Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020, 2019 | 55 | 2019 |
Predicted cellular immunity population coverage gaps for SARS-CoV-2 subunit vaccines and their augmentation by compact peptide sets G Liu, B Carter, DK Gifford Cell systems 12 (1), 102-107. e4, 2021 | 47 | 2021 |
Visualizing complex feature interactions and feature sharing in genomic deep neural networks G Liu, H Zeng, DK Gifford BMC bioinformatics 20, 1-14, 2019 | 23 | 2019 |
Computational counterselection identifies nonspecific therapeutic biologic candidates SD Saksena, G Liu, C Banholzer, G Horny, S Ewert, DK Gifford Cell Reports Methods 2 (7), 2022 | 11 | 2022 |
Machine learning based antibody design DK Gifford, H Zeng, G Liu US Patent App. 16/171,596, 2019 | 11 | 2019 |
Visualizing feature maps in deep neural networks using deepresolve. a genomics case study G Liu, D Gifford Proceedings of the International Conference on Machine Learning—Workshop on …, 2017 | 10 | 2017 |
A pan-variant mRNA-LNP T cell vaccine protects HLA transgenic mice from mortality after infection with SARS-CoV-2 Beta B Carter, P Huang, G Liu, Y Liang, PJC Lin, BH Peng, LGA McKay, ... Frontiers in immunology 14, 1135815, 2023 | 7 | 2023 |
Maximum n-times Coverage for Vaccine Design G Liu, A Dimitrakakis, B Carter, D Gifford International Conference on Learning Representations (ICLR 2022), 2021 | 7 | 2021 |
Bridging Recommendation and Marketing via Recurrent Intensity Modeling Y Ma, G Liu, A Deoras International Conference on Learning Representations (ICLR 2022), 2021 | 3 | 2021 |
Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing G Liu, R Wu, HT Cheng, J Wang, J Ooi, L Li, A Li, WLS Li, C Boutilier, ... Deep Reinforcement Learning workshop at NeurIPS, 2019, 2020 | 3 | 2020 |
Information Condensing Active Learning S Jain, G Liu, D Gifford arXiv preprint arXiv:2002.07916, 2020 | 2 | 2020 |
Beyond predictive modeling: new computational aspects for deep learning based biological applications G Liu Massachusetts Institute of Technology, 2020 | 2 | 2020 |
Sequence-graph duality: Unifying user modeling with self-attention for sequential recommendation Z Shui, G Liu, A Deoras, G Karypis New Frontiers in Graph Learning Workshop, NeurIPS 2022, 2022 | 1 | 2022 |
Optimal Design for Human Feedback S Mukherjee, A Lalitha, K Kalantari, A Deshmukh, G Liu, Y Ma, B Kveton arXiv preprint arXiv:2404.13895, 2024 | | 2024 |
Experimental Design for Active Transductive Inference in Large Language Models S Mukherjee, G Liu, A Deshmukh, A Lalitha, Y Ma, B Kveton arXiv preprint arXiv:2404.08846, 2024 | | 2024 |
Pessimistic Off-Policy Multi-Objective Optimization S Alizadeh, A Bhargava, K Gopalswamy, L Jain, B Kveton, G Liu 27th International Conference on Artificial Intelligence and Statistics …, 2023 | | 2023 |
Recurrent Intensity Modeling for User Recommendation and Online Matching Y Ma, G Liu, A Deoras Time Series Workshop at ICML, 2021, 2021 | | 2021 |