Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDRuichu Cai
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j71]Ruichu Cai, Yunjin Wu, Xiaokai Huang, Wei Chen, Tom Z. J. Fu, Zhifeng Hao:
Granger causal representation learning for groups of time series. Sci. China Inf. Sci. 67(5) (2024)- [j70]Ruichu Cai, Ruming Lu, Wei Chen
, Zhifeng Hao:
Counterfactual contextual bandit for recommendation under delayed feedback. Neural Comput. Appl. 36(23): 14599-14613 (2024) - [j69]Ruichu Cai, Weilin Chen, Zeqin Yang, Shu Wan, Chen Zheng, Xiaoqing Yang, Jiecheng Guo:
Long-term causal effects estimation via latent surrogates representation learning. Neural Networks 176: 106336 (2024) - [j68]Wen Wen, Shiyuan Wu, Ruichu Cai, Zhifeng Hao:
Cross-KG Link Prediction by Learning Substructural Semantics. Neural Process. Lett. 56(1): 40 (2024) - [j67]Zijian Li, Ruichu Cai, Tom Z. J. Fu, Zhifeng Hao, Kun Zhang:
Transferable Time-Series Forecasting Under Causal Conditional Shift. IEEE Trans. Pattern Anal. Mach. Intell. 46(4): 1932-1949 (2024) - [j66]Lijuan Wang, Shaomin Chen, Ming Yin, Zhifeng Hao, Ruichu Cai:
Block diagonal representation learning with local invariance for face clustering. Soft Comput. 28(13-14): 8133-8149 (2024) - [j65]Ruichu Cai, Fengzhu Wu, Zijian Li, Pengfei Wei, Lingling Yi, Kun Zhang:
Graph Domain Adaptation: A Generative View. ACM Trans. Knowl. Discov. Data 18(3): 60:1-60:24 (2024) - [j64]Ruichu Cai, Siyu Wu, Jie Qiao, Zhifeng Hao, Keli Zhang, Xi Zhang:
THPs: Topological Hawkes Processes for Learning Causal Structure on Event Sequences. IEEE Trans. Neural Networks Learn. Syst. 35(1): 479-493 (2024) - [j63]Zijian Li, Ruichu Cai, Fengzhu Wu, Sili Zhang, Hao Gu, Yuexing Hao, Yuguang Yan:
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2628-2639 (2024) - [c67]Yuguang Yan, Yuanlin Chen, Shibo Wang, Hanrui Wu, Ruichu Cai:
Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion. AAAI 2024: 9232-9240 - [c66]Ruichu Cai, Yuxuan Zhu, Jie Qiao, Zefeng Liang, Furui Liu, Zhifeng Hao:
Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples. AAAI 2024: 11132-11140 - [c65]Yuguang Yan, Zhihao Xu, Canlin Yang, Jie Zhang, Ruichu Cai, Michael Kwok-Po Ng:
An Optimal Transport View for Subspace Clustering and Spectral Clustering. AAAI 2024: 16281-16289 - [c64]Yuguang Yan, Zeqin Yang, Weilin Chen, Ruichu Cai, Zhifeng Hao, Michael Kwok-Po Ng:
Exploiting Geometry for Treatment Effect Estimation via Optimal Transport. AAAI 2024: 16290-16298 - [c63]Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang:
Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants. AAAI 2024: 20353-20361 - [c62]Yuequn Liu, Ruichu Cai, Wei Chen, Jie Qiao, Yuguang Yan, Zijian Li, Keli Zhang, Zhifeng Hao:
TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences. AAAI 2024: 20491-20499 - [c61]Jie Qiao, Zhengming Chen, Jianhua Yu, Ruichu Cai, Zhifeng Hao:
Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model. AAAI 2024: 20516-20523 - [c60]Jie Qiao, Yu Xiang, Zhengming Chen, Ruichu Cai, Zhifeng Hao:
Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis. AAAI 2024: 20524-20531 - [c59]Bingfeng Chen, Qihan Ouyang, Yongqi Luo, Boyan Xu, Ruichu Cai, Zhifeng Hao:
S²GSL: Incorporating Segment to Syntactic Enhanced Graph Structure Learning for Aspect-based Sentiment Analysis. ACL (1) 2024: 13366-13379 - [c58]Qingwen Lin, Boyan Xu, Zhengting Huang, Ruichu Cai:
From Large to Tiny: Distilling and Refining Mathematical Expertise for Math Word Problems with Weakly Supervision. ICIC (LNAI 6) 2024: 251-262 - [c57]Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng:
Automating the Selection of Proxy Variables of Unmeasured Confounders. ICML 2024 - [c56]Xuexin Chen, Ruichu Cai, Zhengting Huang, Yuxuan Zhu, Julien Horwood, Zhifeng Hao, Zijian Li, José Miguel Hernández-Lobato:
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation. ICML 2024 - [c55]Weilin Chen, Ruichu Cai, Zeqin Yang, Jie Qiao, Yuguang Yan, Zijian Li, Zhifeng Hao:
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning. ICML 2024 - [c54]Yuguang Yan, Hao Zhou, Zeqin Yang, Weilin Chen, Ruichu Cai, Zhifeng Hao:
Reducing Balancing Error for Causal Inference via Optimal Transport. ICML 2024 - [i54]Ruichu Cai, Siyang Huang, Jie Qiao, Wei Chen, Yan Zeng, Keli Zhang, Fuchun Sun, Yang Yu, Zhifeng Hao:
Learning by Doing: An Online Causal Reinforcement Learning Framework with Causal-Aware Policy. CoRR abs/2402.04869 (2024) - [i53]Xuexin Chen, Ruichu Cai, Zhengting Huang, Yuxuan Zhu, Julien Horwood, Zhifeng Hao, Zijian Li, José Miguel Hernández-Lobato:
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation. CoRR abs/2402.08845 (2024) - [i52]Xuexin Chen, Ruichu Cai, Kaitao Zheng, Zhifan Jiang, Zhengting Huang, Zhifeng Hao, Zijian Li:
Unifying Invariance and Spuriousity for Graph Out-of-Distribution via Probability of Necessity and Sufficiency. CoRR abs/2402.09165 (2024) - [i51]Zijian Li, Ruichu Cai, Zhenhui Yang, Haiqin Huang, Guangyi Chen, Yifan Shen, Zhengming Chen, Xiangchen Song, Zhifeng Hao, Kun Zhang:
When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting. CoRR abs/2402.12767 (2024) - [i50]Zijian Li, Ruichu Cai, Haiqin Huang, Sili Zhang, Yuguang Yan, Zhifeng Hao, Zhenghua Dong:
Debiased Model-based Interactive Recommendation. CoRR abs/2402.15819 (2024) - [i49]Qingwen Lin, Boyan Xu, Zhengting Huang, Ruichu Cai:
From Large to Tiny: Distilling and Refining Mathematical Expertise for Math Word Problems with Weakly Supervision. CoRR abs/2403.14390 (2024) - [i48]Jie Qiao, Yu Xiang, Zhengming Chen, Ruichu Cai, Zhifeng Hao:
Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis. CoRR abs/2403.16523 (2024) - [i47]Weilin Chen, Ruichu Cai, Zeqin Yang, Jie Qiao, Yuguang Yan, Zijian Li, Zhifeng Hao:
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning. CoRR abs/2405.03342 (2024) - [i46]Zijian Li, Yifan Shen, Kaitao Zheng, Ruichu Cai, Xiangchen Song, Mingming Gong, Zhifeng Hao, Zhengmao Zhu, Guangyi Chen, Kun Zhang:
On the Identification of Temporally Causal Representation with Instantaneous Dependence. CoRR abs/2405.15325 (2024) - [i45]Ruichu Cai, Zhifang Jiang, Zijian Li, Weilin Chen, Xuexin Chen, Zhifeng Hao, Yifan Shen, Guangyi Chen, Kun Zhang:
From Orthogonality to Dependency: Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals. CoRR abs/2405.16083 (2024) - [i44]Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng:
Automating the Selection of Proxy Variables of Unmeasured Confounders. CoRR abs/2405.16130 (2024) - [i43]Bingfeng Chen, Qihan Ouyang, Yongqi Luo, Boyan Xu, Ruichu Cai, Zhifeng Hao:
S2GSL: Incorporating Segment to Syntactic Enhanced Graph Structure Learning for Aspect-based Sentiment Analysis. CoRR abs/2406.02902 (2024) - [i42]Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang:
Learning Discrete Latent Variable Structures with Tensor Rank Conditions. CoRR abs/2406.07020 (2024) - [i41]Zeqin Yang, Weilin Chen, Ruichu Cai, Yuguang Yan, Zhifeng Hao, Zhipeng Yu, Zhichao Zou, Zhen Peng, Jiecheng Guo:
Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights. CoRR abs/2406.19195 (2024) - [i40]Jiafan Zhuang, Gaofei Han, Zihao Xia, Boxi Wang, Wenji Li, Dongliang Wang, Zhifeng Hao, Ruichu Cai, Zhun Fan:
Robust Policy Learning for Multi-UAV Collision Avoidance with Causal Feature Selection. CoRR abs/2407.04056 (2024) - [i39]Jiafan Zhuang, Zihao Xia, Gaofei Han, Boxi Wang, Wenji Li, Dongliang Wang, Zhifeng Hao, Ruichu Cai, Zhun Fan:
Collision Avoidance for Multiple UAVs in Unknown Scenarios with Causal Representation Disentanglement. CoRR abs/2407.04064 (2024) - [i38]Xuexin Chen, Ruichu Cai, Kaitao Zheng, Zhifan Jiang, Zhengting Huang, Zhifeng Hao, Zijian Li:
Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency. CoRR abs/2407.15273 (2024) - 2023
- [j62]Ruichu Cai, Liting Huang, Wei Chen, Jie Qiao, Zhifeng Hao:
Learning dynamic causal mechanisms from non-stationary data. Appl. Intell. 53(5): 5437-5448 (2023) - [j61]Zhifeng Hao, Junbin Chen, Wen Wen, Biao Wu, Ruichu Cai:
A selection-pattern-aware recommendation model with colored-motif attention network. Neurocomputing 538: 126178 (2023) - [j60]Yanshan Xiao, Liangwang Zhang, Bo Liu, Ruichu Cai, Zhifeng Hao:
Multi-task ordinal regression with labeled and unlabeled data. Inf. Sci. 649: 119669 (2023) - [j59]Wen Wen, Wencui Wang, Zhifeng Hao, Ruichu Cai:
Factorizing time-heterogeneous Markov transition for temporal recommendation. Neural Networks 159: 84-96 (2023) - [j58]Jian Zhu, Qingwu Zhang, Lunke Fei, Ruichu Cai, Yuan Xie, Bin Sheng, Xiaokang Yang:
FFFN: Frame-By-Frame Feedback Fusion Network for Video Super-Resolution. IEEE Trans. Multim. 25: 6821-6835 (2023) - [j57]Yan Zeng, Zhifeng Hao, Ruichu Cai, Feng Xie, Libo Huang, Shohei Shimizu:
Nonlinear Causal Discovery for High-Dimensional Deterministic Data. IEEE Trans. Neural Networks Learn. Syst. 34(5): 2234-2245 (2023) - [c53]Ruichu Cai, Zeqin Yang, Weilin Chen, Yuguang Yan, Zhifeng Hao:
Generalization Bound for Estimating Causal Effects from Observational Network Data. CIKM 2023: 163-172 - [c52]Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang:
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants. ICML 2023: 3380-3407 - [c51]Zhifeng Hao, Haipeng Zhu, Wei Chen, Ruichu Cai:
Latent Causal Dynamics Model for Model-Based Reinforcement Learning. ICONIP (2) 2023: 219-230 - [c50]Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai:
Some General Identification Results for Linear Latent Hierarchical Causal Structure. IJCAI 2023: 3568-3576 - [c49]Jie Qiao, Ruichu Cai, Siyu Wu, Yu Xiang, Keli Zhang, Zhifeng Hao:
Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences. IJCAI 2023: 5702-5710 - [c48]Zijian Li, Ruichu Cai, Guangyi Chen, Boyang Sun, Zhifeng Hao, Kun Zhang:
Subspace Identification for Multi-Source Domain Adaptation. NeurIPS 2023 - [i37]Yan Zeng, Ruichu Cai, Fuchun Sun, Libo Huang, Zhifeng Hao:
A Survey on Causal Reinforcement Learning. CoRR abs/2302.05209 (2023) - [i36]Jie Qiao, Ruichu Cai, Siyu Wu, Yu Xiang, Keli Zhang, Zhifeng Hao:
Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences. CoRR abs/2305.05986 (2023) - [i35]Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang:
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants. CoRR abs/2305.19582 (2023) - [i34]Ruichu Cai, Yuequn Liu, Wei Chen, Jie Qiao, Yuguang Yan, Zijian Li, Keli Zhang, Zhifeng Hao:
TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences. CoRR abs/2306.14114 (2023) - [i33]Yujia Zheng, Biwei Huang, Wei Chen, Joseph D. Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang:
Causal-learn: Causal Discovery in Python. CoRR abs/2307.16405 (2023) - [i32]Ruichu Cai, Zeqin Yang, Weilin Chen, Yuguang Yan, Zhifeng Hao:
Generalization bound for estimating causal effects from observational network data. CoRR abs/2308.04011 (2023) - [i31]Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang:
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. CoRR abs/2308.06718 (2023) - [i30]Zijian Li, Ruichu Cai, Guangyi Chen, Boyang Sun, Zhifeng Hao, Kun Zhang:
Subspace Identification for Multi-Source Domain Adaptation. CoRR abs/2310.04723 (2023) - [i29]Zijian Li, Zunhong Xu, Ruichu Cai, Zhenhui Yang, Yuguang Yan, Zhifeng Hao, Guangyi Chen, Kun Zhang:
Identifying Semantic Component for Robust Molecular Property Prediction. CoRR abs/2311.04837 (2023) - [i28]Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang:
Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants. CoRR abs/2312.11934 (2023) - [i27]Jie Qiao, Zhengming Chen, Jianhua Yu, Ruichu Cai, Zhifeng Hao:
Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model. CoRR abs/2312.12206 (2023) - [i26]Ruichu Cai, Yuxuan Zhu, Jie Qiao, Zefeng Liang, Furui Liu, Zhifeng Hao:
Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples. CoRR abs/2312.13628 (2023) - 2022
- [j56]Lijuan Wang, Lin Zhang, Ming Yin, Zhifeng Hao, Ruichu Cai, Wen Wen:
Double embedding-transfer-based multi-view spectral clustering. Expert Syst. Appl. 210: 118374 (2022) - [j55]Wei Chen, Jibin Chen, Ruichu Cai, Yuequn Liu, Zhifeng Hao:
Learning granger causality for non-stationary Hawkes processes. Neurocomputing 468: 22-32 (2022) - [j54]Ruichu Cai, Zhaolong Lin, Wei Chen, Zhifeng Hao:
Shared state space model for background information extraction and time series prediction. Neurocomputing 468: 85-96 (2022) - [j53]Zhifeng Hao, Junhao Chen, Wen Wen, Biao Wu, Ruichu Cai:
Motif-based memory networks for complex-factoid question answering. Neurocomputing 485: 12-21 (2022) - [j52]Jie Qiao, Yiming Bai, Ruichu Cai, Zhifeng Hao:
Causal discovery from multi-domain data using the independence of modularities. Neural Comput. Appl. 34(3): 1939-1949 (2022) - [j51]Wei Chen, Ruichu Cai, Kun Zhang, Zhifeng Hao:
Causal Discovery in Linear Non-Gaussian Acyclic Model With Multiple Latent Confounders. IEEE Trans. Neural Networks Learn. Syst. 33(7): 2816-2827 (2022) - [c47]Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Kun Zhang, Ruichu Cai:
Identification of Linear Latent Variable Model with Arbitrary Distribution. AAAI 2022: 6350-6357 - [c46]Yuequn Liu, Wenhui Zhu, Jie Qiao, Zhiyi Huang, Yu Xiang, Xuanzhi Chen, Wei Chen, Ruichu Cai:
Causal Alignment Based Fault Root Causes Localization for Wireless Network. ICASSP 2022: 9311-9315 - [i25]Ruichu Cai, Fengzhu Wu, Zijian Li, Jie Qiao, Wei Chen, Yuexing Hao, Hao Gu:
REST: Debiased Social Recommendation via Reconstructing Exposure Strategies. CoRR abs/2201.04952 (2022) - [i24]Zijian Li, Ruichu Cai, Jiawei Chen, Yuguan Yan, Wei Chen, Keli Zhang, Junjian Ye:
Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance. CoRR abs/2205.03554 (2022) - [i23]Ruichu Cai, Weilin Chen, Zeqin Yang, Shu Wan, Chen Zheng, Xiaoqing Yang, Jiecheng Guo:
Long-term Causal Effects Estimation via Latent Surrogates Representation Learning. CoRR abs/2208.04589 (2022) - [i22]Ruichu Cai, Yuxuan Zhu, Xuexin Chen, Yuan Fang, Min Wu, Jie Qiao, Zhifeng Hao:
On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach. CoRR abs/2212.07056 (2022) - 2021
- [j50]Jie Qiao, Yiming Bai, Ruichu Cai, Zhifeng Hao:
Learning causal structures using hidden compact representation. Neurocomputing 463: 328-333 (2021) - [j49]Jian Zhu, Silong Li, Ruichu Cai, Zhifeng Hao, Guoheng Huang, Bin Sheng, Enhua Wu:
Compensating the vorticity loss during advection with an adaptive vorticity confinement force. Comput. Animat. Virtual Worlds 32(1) (2021) - [j48]Liting Huang, Zhiying Jiang, Ruichu Cai, Li Li, Qinqun Chen, Jiaming Hong, Zhifeng Hao, Hang Wei:
Investigating the interpretability of fetal status assessment using antepartum cardiotocographic records. BMC Medical Informatics Decis. Mak. 21(1): 355 (2021) - [j47]Zhifeng Hao, Di Lv, Zijian Li, Ruichu Cai, Wen Wen, Boyan Xu:
Semi-supervised disentangled framework for transferable named entity recognition. Neural Networks 135: 127-138 (2021) - [j46]Zijian Li, Ruichu Cai, Hong Wei Ng, Marianne Winslett, Tom Z. J. Fu, Boyan Xu, Xiaoyan Yang, Zhenjie Zhang:
Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems. ACM Trans. Intell. Syst. Technol. 12(2): 23:1-23:21 (2021) - [j45]Jie Qiao, Ruichu Cai, Kun Zhang, Zhenjie Zhang, Zhifeng Hao:
Causal Discovery with Confounding Cascade Nonlinear Additive Noise Models. ACM Trans. Intell. Syst. Technol. 12(6): 80:1-80:28 (2021) - [j44]Zhifeng Hao, Di Wu, Yuan Fang, Min Wu, Ruichu Cai, Xiaoli Li:
Prediction of Synthetic Lethal Interactions in Human Cancers Using Multi-View Graph Auto-Encoder. IEEE J. Biomed. Health Informatics 25(10): 4041-4051 (2021) - [c45]Ruichu Cai, Hao Zhang, Wen Liu, Shenghua Gao, Zhifeng Hao:
Appearance-Motion Memory Consistency Network for Video Anomaly Detection. AAAI 2021: 938-946 - [c44]Ruichu Cai, Jiawei Chen, Zijian Li, Wei Chen, Keli Zhang, Junjian Ye, Zhuozhang Li, Xiaoyan Yang, Zhenjie Zhang:
Time Series Domain Adaptation via Sparse Associative Structure Alignment. AAAI 2021: 6859-6867 - [c43]Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao:
Causal Discovery with Multi-Domain LiNGAM for Latent Factors. CAWS 2021: 1-4 - [c42]Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao:
Causal Discovery with Multi-Domain LiNGAM for Latent Factors. IJCAI 2021: 2097-2103 - [c41]Ruichu Cai, Jinjie Yuan, Boyan Xu, Zhifeng Hao:
SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL. NeurIPS 2021: 7664-7676 - [c40]Petar Stojanov, Zijian Li, Mingming Gong, Ruichu Cai, Jaime G. Carbonell, Kun Zhang:
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? NeurIPS 2021: 24791-24803 - [i21]Wei Chen, Kun Zhang, Ruichu Cai, Biwei Huang, Joseph D. Ramsey, Zhifeng Hao, Clark Glymour:
FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders. CoRR abs/2103.14238 (2021) - [i20]Ruichu Cai, Siyu Wu, Jie Qiao, Zhifeng Hao, Keli Zhang, Xi Zhang:
THP: Topological Hawkes Processes for Learning Granger Causality on Event Sequences. CoRR abs/2105.10884 (2021) - [i19]Ruichu Cai, Weilin Chen, Jie Qiao, Zhifeng Hao:
On the Role of Entropy-based Loss for Learning Causal Structures with Continuous Optimization. CoRR abs/2106.02835 (2021) - [i18]Ruichu Cai, Fengzhu Wu, Zijian Li, Pengfei Wei, Lingling Yi, Kun Zhang:
Graph Domain Adaptation: A Generative View. CoRR abs/2106.07482 (2021) - [i17]Ruichu Cai, Jinjie Yuan, Boyan Xu, Zhifeng Hao:
SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL. CoRR abs/2111.00653 (2021) - [i16]Zijian Li, Ruichu Cai, Tom Z. J. Fu, Kun Zhang:
Transferable Time-Series Forecasting under Causal Conditional Shift. CoRR abs/2111.03422 (2021) - [i15]Zijian Li, Ruichu Cai, Fengzhu Wu, Sili Zhang, Hao Gu, Yuexing Hao, Yuguang:
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations. CoRR abs/2111.07378 (2021) - [i14]Wei Chen, Yunjin Wu, Ruichu Cai, Yueguo Chen, Zhifeng Hao:
CCSL: A Causal Structure Learning Method from Multiple Unknown Environments. CoRR abs/2111.09666 (2021) - [i13]Xuexin Chen, Ruichu Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao:
Motif Graph Neural Network. CoRR abs/2112.14900 (2021) - 2020
- [j43]Ruichu Cai, Xuexin Chen, Yuan Fang, Min Wu, Yuexing Hao, Jonathan D. Wren:
Dual-dropout graph convolutional network for predicting synthetic lethality in human cancers. Bioinform. 36(16): 4458-4465 (2020) - [j42]Jian Zhu, Zhuo Yang, Hanqiu Sun, Enhua Wu, Ruichu Cai, Zhifeng Hao:
Detail-preserving smoke simulation using an efficient high-order numerical scheme. Sci. China Inf. Sci. 63(6) (2020) - [j41]Lijuan Wang, Jiawen Huang, Ming Yin, Ruichu Cai, Zhifeng Hao:
Block diagonal representation learning for robust subspace clustering. Inf. Sci. 526: 54-67 (2020) - [j40]Jian Zhu, Silong Li, Ruichu Cai, Zhifeng Hao, Guoheng Huang, Bin Sheng, Enhua Wu:
Animating turbulent fluid with a robust and efficient high-order advection method. Comput. Animat. Virtual Worlds 31(4-5) (2020) - [j39]Wei Chen, Ruichu Cai, Zhifeng Hao, Chang Yuan, Feng Xie:
Mining hidden non-redundant causal relationships in online social networks. Neural Comput. Appl. 32(11): 6913-6923 (2020) - [j38]Biao Wu, Wen Wen, Zhifeng Hao, Ruichu Cai:
Multi-context aware user-item embedding for recommendation. Neural Networks 124: 86-94 (2020) - [j37]Yan Zeng, Zhifeng Hao, Ruichu Cai, Feng Xie, Liang Ou, Ruihui Huang:
A causal discovery algorithm based on the prior selection of leaf nodes. Neural Networks 124: 130-145 (2020) - [j36]Ruichu Cai, Jincheng Ye, Jie Qiao, Huiyuan Fu, Zhifeng Hao:
FOM: Fourth-order moment based causal direction identification on the heteroscedastic data. Neural Networks 124: 193-201 (2020) - [j35]Feng Xie, Ruichu Cai, Yan Zeng, Jiantao Gao, Zhifeng Hao:
An Efficient Entropy-Based Causal Discovery Method for Linear Structural Equation Models With IID Noise Variables. IEEE Trans. Neural Networks Learn. Syst. 31(5): 1667-1680 (2020) - [j34]Ruichu Cai, Jiahao Li, Zhenjie Zhang, Xiaoyan Yang, Zhifeng Hao:
DACH: Domain Adaptation Without Domain Information. IEEE Trans. Neural Networks Learn. Syst. 31(12): 5055-5067 (2020) - [c39]Ruichu Cai, Zhihao Liang, Boyan Xu, Zijian Li, Yuexing Hao, Yao Chen:
TAG : Type Auxiliary Guiding for Code Comment Generation. ACL 2020: 291-301 - [c38]Kailin Tang, Zhifeng Hao, Ruichu Cai, Tom Z. J. Fu, Yin Yang, Li Wang, Marianne Winslett, Zhenjie Zhang: