Neural Model-Based Reinforcement Learning for Recommendation. - Xinshi Chen; Shuang Li 002; Hui Li 061; Shaohua Jiang; Yuan Qi 001; Le Song (CoRR, 2018)

Generative Adversarial User Model for Reinforcement Learning Based Recommendation System. - Xinshi Chen; Shuang Li 002; Hui Li 061; Shaohua Jiang; Yuan Qi 001; Le Song (ICML, 2019)

Particle Flow Bayes' Rule. - Xinshi Chen; Hanjun Dai; Le Song (ICML, 2019)

Parametric FEM for Shape Optimization applied to Golgi Stack. - Xinshi Chen; Eric Tsz Shun Chung (CoRR, 2019)

Meta Particle Flow for Sequential Bayesian Inference. - Xinshi Chen; Hanjun Dai; Le Song (CoRR, 2019)

GLAD: Learning Sparse Graph Recovery. - Harsh Shrivastava 001; Xinshi Chen; Binghong Chen; Guanghui Lan; Srinivas Aluru; Le Song (CoRR, 2019)

Can Graph Neural Networks Help Logic Reasoning? - Yuyu Zhang; Xinshi Chen; Yuan Yang; Arun Ramamurthy; Bo Li; Yuan Qi 001; Le Song (CoRR, 2019)

Review: Ordinary Differential Equations For Deep Learning. - Xinshi Chen (CoRR, 2019)

RNA Secondary Structure Prediction By Learning Unrolled Algorithms. - Xinshi Chen; Yu Li 006; Ramzan Umarov; Xin Gao 001; Le Song (ICLR, 2020)

GLAD: Learning Sparse Graph Recovery. - Harsh Shrivastava 001; Xinshi Chen; Binghong Chen; Guanghui Lan; Srinivas Aluru; Han Liu 001; Le Song (ICLR, 2020)

Efficient Probabilistic Logic Reasoning with Graph Neural Networks. - Yuyu Zhang; Xinshi Chen; Yuan Yang; Arun Ramamurthy; Bo Li; Yuan Qi 001; Le Song (ICLR, 2020)

Learning To Stop While Learning To Predict. - Xinshi Chen; Hanjun Dai; Yu Li 006; Xin Gao 001; Le Song (ICML, 2020)

Understanding Deep Architecture with Reasoning Layer. - Xinshi Chen; Yufei Zhang 001; Christoph Reisinger; Le Song (NeurIPS, 2020)

Understanding Deep Architectures with Reasoning Layer. - Xinshi Chen; Yufei Zhang 001; Christoph Reisinger; Le Song (CoRR, 2020)

Multi-task Learning of Order-Consistent Causal Graphs. - Xinshi Chen; Haoran Sun; Caleb Ellington; Eric P. Xing; Le Song (NeurIPS, 2021)

Efficient Dynamic Graph Representation Learning at Scale. - Xinshi Chen; Yan Zhu; Haowen Xu; Mengyang Liu; Liang Xiong; Muhan Zhang; Le Song (CoRR, 2021)

Provable Learning-based Algorithm For Sparse Recovery. - Xinshi Chen; Haoran Sun; Le Song (ICLR, 2022)

uGLAD: Sparse graph recovery by optimizing deep unrolled networks. - Harsh Shrivastava 001; Urszula Chajewska; Robin Abraham; Xinshi Chen (CoRR, 2022)

Graph Condensation via Receptive Field Distribution Matching. - Mengyang Liu; Shanchuan Li; Xinshi Chen; Le Song (CoRR, 2022)

Duality Between Deep Learning And Algorithm Design. - Xinshi Chen (2022)

Protenix-Mini: Efficient Structure Predictor via Compact Architecture, Few-Step Diffusion and Switchable pLM. - Chengyue Gong; Xinshi Chen; Yuxuan Zhang; Yuxuan Song; Hao Zhou; Wenzhi Xiao (CoRR, 2025)