| Generative adversarial user model for reinforcement learning based recommendation system X Chen, S Li, H Li, S Jiang, Y Qi, L Song International Conference on Machine Learning, 1052--1061, 2018 | 263 | 2018 |
| Efficient probabilistic logic reasoning with graph neural networks Y Zhang, X Chen, Y Yang, A Ramamurthy, B Li, Y Qi, L Song International Conference on Learning Representations 2020, 2019 | 148 | 2019 |
| RNA Secondary Structure Prediction By Learning Unrolled Algorithms X Chen, Y Li, R Umarov, X Gao, L Song International Conference on Learning Representations 2020, 2019 | 110 | 2019 |
| A distinct class of vesicles derived from the trans‐Golgi mediates secretion of xylogalacturonan in the root border cell P Wang, X Chen, C Goldbeck, E Chung, BH Kang The Plant Journal 92 (4), 596-610, 2017 | 65 | 2017 |
| Learning to stop while learning to predict X Chen, H Dai, Y Li, X Gao, L Song International conference on machine learning, 1520-1530, 2020 | 53 | 2020 |
| GLAD: Learning Sparse Graph Recovery H Shrivastava, X Chen, B Chen, G Lan, S Aluru, L Song International Conference on Learning Representations 2020, 2019 | 40 | 2019 |
| Graph condensation via receptive field distribution matching M Liu, S Li, X Chen, L Song arXiv preprint arXiv:2206.13697, 2022 | 33 | 2022 |
| Understanding deep architecture with reasoning layer X Chen, Y Zhang, C Reisinger, L Song Advances in Neural Information Processing Systems 33, 1240-1252, 2020 | 19 | 2020 |
| Can graph neural networks help logic reasoning? Y Zhang, X Chen, Y Yang, A Ramamurthy, B Li, Y Qi, L Song arXiv preprint arXiv:1906.02111, 2019 | 19 | 2019 |
| Multi-task learning of order-consistent causal graphs X Chen, H Sun, C Ellington, E Xing, L Song Advances in Neural Information Processing Systems 34, 11083-11095, 2021 | 15 | 2021 |
| uGLAD: sparse graph recovery by optimizing deep unrolled networks H Shrivastava, U Chajewska, R Abraham, X Chen arXiv preprint arXiv:2205.11610, 2022 | 12 | 2022 |
| Particle Flow Bayes' Rule X Chen, H Dai, L Song International Conference on Machine Learning, 1022--1031, 2019 | 12* | 2019 |
| A deep learning approach to recover conditional independence graphs H Shrivastava, U Chajewska, R Abraham, X Chen NeurIPS 2022 Workshop: New Frontiers in Graph Learning, 2022 | 11 | 2022 |
| Ordinary differential equations for deep learning X Chen arXiv preprint arXiv:1911.00502, 2019 | 10* | 2019 |
| Efficient dynamic graph representation learning at scale X Chen, Y Zhu, H Xu, M Liu, L Xiong, M Zhang, L Song arXiv preprint arXiv:2112.07768, 2021 | 7 | 2021 |
| A framework for differentiable discovery of graph algorithms H Dai, X Chen, Y Li, X Gao, L Song | 3 | 2021 |
| Towards Structured Prediction in Bioinformatics with Deep Learning Y Li arXiv preprint arXiv:2008.11546, 2020 | 1 | 2020 |
| Duality Between Deep Learning And Algorithm Design. X Chen Georgia Institute of Technology, Atlanta, GA, USA, 2022 | | 2022 |
| Provable Learning-based Algorithm For Sparse Recovery X Chen, H Sun, L Song International Conference on Learning Representations, 2022 | | 2022 |
| Parametric FEM for Shape Optimization applied to Golgi Stack X Chen, E Chung arXiv preprint arXiv:1902.00619, 2017 | | 2017 |
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
