Xiao Shou - RankMe

19 papers A* 6Journal 6Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation. AAAI Yanna Ding, Zijie Huang, Xiao Shou, Yihang Guo, Yizhou Sun, Jianxi Gao
2025	J	`jnl`	Gradient Flow Matching for Learning Update Dynamics in Neural Network Training. CoRR Xiao Shou, Yanna Ding, Jianxi Gao
2025	J	`jnl`	Less is More: Efficient Weight Farcasting with 1-Layer Neural Network. CoRR Xiao Shou, Debarun Bhattacharjya, Yanna Ding, Chen Zhao, Rui Li, Jianxi Gao
2025	—	`conf`	SIMBA UQ: Similarity-Based Aggregation for Uncertainty Quantification in Large Language Models. EMNLP (Findings) Debarun Bhattacharjya, Balaji Ganesan, Junkyu Lee, Radu Marinescu, Katsiaryna Mirylenka, Michael R. Glass, Xiao Shou
2025	J	`jnl`	SIMBA UQ: Similarity-Based Aggregation for Uncertainty Quantification in Large Language Models. CoRR Debarun Bhattacharjya, Balaji Ganesan, Junkyu Lee, Radu Marinescu, Katsiaryna Mirylenka, Michael R. Glass, Xiao Shou
2025	J	`jnl`	Unified Flow Matching for Long Horizon Event Forecasting. CoRR Xiao Shou
2024	J	`jnl`	Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation. CoRR Yanna Ding, Zijie Huang, Xiao Shou, Yihang Guo, Yizhou Sun, Jianxi Gao
2024	J	`jnl`	Self-Supervised Contrastive Pre-Training for Multivariate Point Processes. CoRR Xiao Shou, Dharmashankar Subramanian, Debarun Bhattacharjya, Tian Gao, Kristin P. Bennett
2023	A*	`conf`	Concurrent Multi-Label Prediction in Event Streams. AAAI Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin P. Bennett
2023	—	`conf`	Influence-Aware Attention for Multivariate Temporal Point Processes. CLeaR Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin P. Bennett
2023	A*	`conf`	Pairwise Causality Guided Transformers for Event Sequences. NeurIPS Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P. Bennett
2023	A*	`conf`	Probabilistic Attention-to-Influence Neural Models for Event Sequences. ICML Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P. Bennett
2023	A*	`conf`	Score-Based Learning of Graphical Event Models with Background Knowledge Augmentation. AAAI Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Xiao Shou
2022	—	`conf`	HMM-Boost: Improved Time Series State Prediction Via Supervised Hidden Markov Models: Case Studies in Epileptic Seizure and Complex Care Management. ICKG Georgios Mavroudeas, Malik Magdon-Ismail, Xiao Shou, Kristin P. Bennett
2022	—	`conf`	HMM-Boost: Improved Time Series State Prediction Via Supervised Hidden Markov Models: Case Studies in Epileptic Seizure and Complex Care Management. ICDM (Workshops) Georgios Mavroudeas, Malik Magdon-Ismail, Xiao Shou, Kristin P. Bennett
2021	A*	`conf`	Causal Inference for Event Pairs in Multivariate Point Processes. NeurIPS Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Xiao Shou, Nicholas Mattei, Kristin P. Bennett
2021	—	`conf`	Match2: hybrid self-organizing map and deep learning strategies for treatment effect estimation. BCB Xiao Shou, Tian Gao, Dharmashankar Subramanian, Kristin P. Bennett
2021	—	`conf`	Predictive Modeling for Complex Care Management. BIBM Georgios Mavroudeas, Nafis Neehal, Xiao Shou, Malik Magdon-Ismail, Jason Nicholas Kuruzovich, Kristin P. Bennett
2019	—	`conf`	Supervised Mixture Models for Population Health. BIBM Xiao Shou, Georgios Mavroudeas, Alexander New, Kofi Arhin, Jason Nicholas Kuruzovich, Malik Magdon-Ismail, Kristin P. Bennett