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2020 – today
- 2022
[b1]Xinshi Chen:
Duality Between Deep Learning And Algorithm Design. Georgia Institute of Technology, Atlanta, GA, USA, 2022- [c9]Xinshi Chen, Haoran Sun, Le Song:
Provable Learning-based Algorithm For Sparse Recovery. ICLR 2022 - [i14]Harsh Shrivastava, Urszula Chajewska, Robin Abraham, Xinshi Chen:
uGLAD: Sparse graph recovery by optimizing deep unrolled networks. CoRR abs/2205.11610 (2022) - [i13]Mengyang Liu, Shanchuan Li, Xinshi Chen, Le Song:
Graph Condensation via Receptive Field Distribution Matching. CoRR abs/2206.13697 (2022) - 2021
- [c8]Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. NeurIPS 2021: 11083-11095 - [i12]Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. CoRR abs/2111.02545 (2021) - [i11]Xinshi Chen, Yan Zhu, Haowen Xu, Mengyang Liu, Liang Xiong, Muhan Zhang, Le Song:
Efficient Dynamic Graph Representation Learning at Scale. CoRR abs/2112.07768 (2021) - 2020
- [c7]Xinshi Chen, Yu Li, Ramzan Umarov, Xin Gao, Le Song:
RNA Secondary Structure Prediction By Learning Unrolled Algorithms. ICLR 2020 - [c6]Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Han Liu, Le Song:
GLAD: Learning Sparse Graph Recovery. ICLR 2020 - [c5]Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song:
Efficient Probabilistic Logic Reasoning with Graph Neural Networks. ICLR 2020 - [c4]Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song:
Learning To Stop While Learning To Predict. ICML 2020: 1520-1530 - [c3]Xinshi Chen, Yufei Zhang, Christoph Reisinger, Le Song:
Understanding Deep Architecture with Reasoning Layer. NeurIPS 2020 - [i10]Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song:
Efficient Probabilistic Logic Reasoning with Graph Neural Networks. CoRR abs/2001.11850 (2020) - [i9]Xinshi Chen, Yu Li, Ramzan Umarov, Xin Gao, Le Song:
RNA Secondary Structure Prediction By Learning Unrolled Algorithms. CoRR abs/2002.05810 (2020) - [i8]Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song:
Learning to Stop While Learning to Predict. CoRR abs/2006.05082 (2020) - [i7]Xinshi Chen, Yufei Zhang, Christoph Reisinger, Le Song:
Understanding Deep Architectures with Reasoning Layer. CoRR abs/2006.13401 (2020)
2010 – 2019
- 2019
- [c2]Xinshi Chen, Hanjun Dai, Le Song:
Particle Flow Bayes' Rule. ICML 2019: 1022-1031 - [c1]Xinshi Chen, Shuang Li, Hui Li, Shaohua Jiang, Yuan Qi, Le Song:
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System. ICML 2019: 1052-1061 - [i6]Xinshi Chen, Eric Tsz Shun Chung:
Parametric FEM for Shape Optimization applied to Golgi Stack. CoRR abs/1902.00619 (2019) - [i5]Xinshi Chen, Hanjun Dai, Le Song:
Meta Particle Flow for Sequential Bayesian Inference. CoRR abs/1902.00640 (2019) - [i4]Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Le Song:
GLAD: Learning Sparse Graph Recovery. CoRR abs/1906.00271 (2019) - [i3]Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song:
Can Graph Neural Networks Help Logic Reasoning? CoRR abs/1906.02111 (2019) - [i2]Xinshi Chen:
Review: Ordinary Differential Equations For Deep Learning. CoRR abs/1911.00502 (2019) - 2018
- [i1]Xinshi Chen, Shuang Li, Hui Li, Shaohua Jiang, Yuan Qi, Le Song:
Neural Model-Based Reinforcement Learning for Recommendation. CoRR abs/1812.10613 (2018)
Coauthor Index
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