| Density of states prediction for materials discovery via contrastive learning from probabilistic embeddings S Kong, F Ricci, D Guevarra, JB Neaton, CP Gomes, JM Gregoire Nature communications 13 (1), 949, 2022 | 44 | 2022 |
| Materials representation and transfer learning for multi-property prediction S Kong, D Guevarra, CP Gomes, JM Gregoire Applied Physics Reviews 8 (2), 2021 | 40 | 2021 |
| CRYSTAL: a multi-agent AI system for automated mapping of materials' crystal structures CP Gomes, J Bai, Y Xue, J Björck, B Rappazzo, S Ament, R Bernstein, ... MRS Communications 9 (2), 600-608, 2019 | 29 | 2019 |
| Disentangled variational autoencoder based multi-label classification with covariance-aware multivariate probit model J Bai, S Kong, C Gomes arXiv preprint arXiv:2007.06126, 2020 | 27 | 2020 |
| Hot-vae: Learning high-order label correlation for multi-label classification via attention-based variational autoencoders W Zhao, S Kong, J Bai, D Fink, C Gomes Proceedings of the AAAI Conference on Artificial Intelligence 35 (17), 15016 …, 2021 | 18 | 2021 |
| Gaussian mixture variational autoencoder with contrastive learning for multi-label classification J Bai, S Kong, CP Gomes International Conference on Machine Learning, 1383-1398, 2022 | 16 | 2022 |
| Deep hurdle networks for zero-inflated multi-target regression: Application to multiple species abundance estimation S Kong, J Bai, JH Lee, D Chen, A Allyn, M Stuart, M Pinsky, K Mills, ... arXiv preprint arXiv:2010.16040, 2020 | 14 | 2020 |
| Detection of pedestrians at night time using learning-based method and head validation Q Liu, J Zhuang, S Kong 2012 IEEE International Conference on Imaging Systems and Techniques …, 2012 | 13 | 2012 |
| Detection of pedestrians for far-infrared automotive night vision systems using learning-based method and head validation Q Liu, J Zhuang, S Kong Measurement Science and Technology 24 (7), 074022, 2013 | 11 | 2013 |
| Shufeng Kong, and Carla P Gomes. Gaussian mixture variational autoencoder with contrastive learning for multi-label classification J Bai International Conference on Machine Learning, 1383-1398, 2022 | 8 | 2022 |
| Shufeng Kong, and Carla Gomes J Bai Disentangled variational autoencoder based multi-label classification with …, 2020 | 8 | 2020 |
| Pretrained cost model for distributed constraint optimization problems Y Deng, S Kong, B An Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 9331-9340, 2022 | 7 | 2022 |
| Multiagent simple temporal problem: The Arc-consistency approach S Kong, JH Lee, S Li Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 7 | 2018 |
| Exploring directional path-consistency for solving constraint networks S Kong, S Li, M Sioutis The Computer Journal 61 (9), 1338-1350, 2018 | 5 | 2018 |
| On tree-preserving constraints S Kong, S Li, Y Li, Z Long Annals of Mathematics and Artificial Intelligence 81, 241-271, 2017 | 5 | 2017 |
| Deep attentive belief propagation: Integrating reasoning and learning for solving constraint optimization problems Y Deng, S Kong, C Liu, B An Advances in Neural Information Processing Systems 35, 25436-25449, 2022 | 4 | 2022 |
| Shufeng Kong, Junwen Bai, Daniel Fink, and Carla Gomes. Hot-vae: Learning high-order label correlation for multi-label classification via attention-based variational autoencoders W Zhao Proceedings of the AAAI Conference on Artificial Intelligence 35, 15016-15024, 2021 | 4 | 2021 |
| Shufeng Kong, Santosh K Suram, R Bruce van Dover, et al CP Gomes, J Bai, Y Xue, J Björck, B Rappazzo, S Ament, R Bernstein Crystal: a multi-agent ai system for automated mapping of materials’ crystal …, 2019 | 4 | 2019 |
| Xtal2DoS: Attention-based crystal to sequence learning for density of states prediction J Bai, Y Du, Y Wang, S Kong, J Gregoire, C Gomes arXiv preprint arXiv:2302.01486, 2023 | 3 | 2023 |
| Critical information quality dimensions of conversational agents for healthcare C Liu, G Peng, S Kong, C Lan, H Zhu Information Research 28 (4), 18, 2023 | 2 | 2023 |
