| Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST W Liu, X Liao, Z Luo, Y Yang, MC Lau, Y Jiao, X Shi, W Zhai, H Ji, ... Nature communications 14 (1), 296, 2023 | 65 | 2023 |
| Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data W Liu, X Liao, Y Yang, H Lin, J Yeong, X Zhou, X Shi, J Liu Nucleic acids research 50 (12), e72-e72, 2022 | 62 | 2022 |
| Schrödinger-Föllmer sampler: sampling without ergodicity J Huang, Y Jiao, L Kang, X Liao, J Liu, Y Liu arXiv preprint arXiv:2106.10880 1, 2021 | 34 | 2021 |
| Rescaled boosting in classification Y Wang, X Liao, S Lin IEEE Transactions on Neural Networks and Learning Systems 30 (9), 2598-2610, 2019 | 14 | 2019 |
| Deep dimension reduction for supervised representation learning J Huang, Y Jiao, X Liao, J Liu, Z Yu IEEE Transactions on Information Theory, 2024 | 9 | 2024 |
| The statistical practice of the GTEx project: from single to multiple tissues X Liao, X Chai, X Shi, LS Chen, J Liu Quantitative Biology 9 (2), 151-167, 2021 | 3 | 2021 |
| Deep dimension reduction for supervised representation learning J Huang, Y Jiao, X Liao, J Liu, Z Yu arXiv preprint arXiv:2006.05865, 2020 | 2 | 2020 |
| Invariant and Sufficient Supervised Representation Learning J Zhu, X Liao, C Li, Y Jiao, J Liu, X Lu 2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023 | 1 | 2023 |
| Toward understanding supervised representation learning with RKHS and GAN X Liao, J Liu, T Wen, Y Jiao, J Huang | 1 | 2020 |
| Multivariate stochastic modeling for transcriptional dynamics with cell-specific latent time using SDEvelo X Liao, L Kang, Y Peng, X Chai, P Xie, C Lin, H Ji, Y Jiao, J Liu Nature Communications 15 (1), 10849, 2024 | | 2024 |
| Schrödinger-Föllmer Sampler J Huang, Y Jiao, L Kang, X Liao, J Liu, Y Liu IEEE Transactions on Information Theory, 2024 | | 2024 |
| Single Cell Gene Expression Prediction via Prototype-based Proximal Neural Factorization X Song, X Liao, H Ye, Y Xu, W Fan, J Liu, T Yu 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2024 | | 2024 |
| SDEvelo: a deep generative approach for transcriptional dynamics with cell-specific latent time and multivariate stochastic modeling J Liu, X Liao, H Ji, Y Jiao, L Kang, Y Peng, X Chai, C Lin | | 2024 |
| Deep estimation for Q⁎ with minimax Bellman error minimization L Kang, X Liao, J Liu, Y Luo Information Sciences 648, 119565, 2023 | | 2023 |
| Author Correction: Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST W Liu, X Liao, Z Luo, Y Yang, MC Lau, Y Jiao, X Shi, W Zhai, H Ji, ... nature communications 14, 2023 | | 2023 |
| Supplementary Notes for “SDEvelo: a deep generative approach for transcriptional dynamics with cell-specific latent time and multivariate stochastic modeling” X Liao, L Kang, Y Peng, X Chai, C Lin, H Ji, Y Jiao, J Liu | | |
