Ruichu Cai

Orcid: 0000-0001-8972-167X

According to our database1, Ruichu Cai authored at least 175 papers between 2006 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Time-aware tensor factorization for temporal recommendation.
Appl. Intell., January, 2025

2024
Motif Graph Neural Network.
IEEE Trans. Neural Networks Learn. Syst., October, 2024

PatchMixing Masked Autoencoders for 3D Point Cloud Self-Supervised Learning.
IEEE Trans. Circuits Syst. Video Technol., October, 2024

Counterfactual contextual bandit for recommendation under delayed feedback.
Neural Comput. Appl., August, 2024

Block diagonal representation learning with local invariance for face clustering.
Soft Comput., July, 2024

Graph Domain Adaptation: A Generative View.
ACM Trans. Knowl. Discov. Data, April, 2024

Transferable Time-Series Forecasting Under Causal Conditional Shift.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2024

TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations.
IEEE Trans. Neural Networks Learn. Syst., February, 2024

Cross-KG Link Prediction by Learning Substructural Semantics.
Neural Process. Lett., February, 2024

THPs: Topological Hawkes Processes for Learning Causal Structure on Event Sequences.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

Time-series domain adaptation via sparse associative structure alignment: Learning invariance and variance.
Neural Networks, 2024

Long-term causal effects estimation via latent surrogates representation learning.
Neural Networks, 2024

Causal-learn: Causal Discovery in Python.
J. Mach. Learn. Res., 2024

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables.
J. Mach. Learn. Res., 2024

Recent Trends of Multimodal Affective Computing: A Survey from NLP Perspective.
CoRR, 2024

Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency.
CoRR, 2024

Collision Avoidance for Multiple UAVs in Unknown Scenarios with Causal Representation Disentanglement.
CoRR, 2024

Robust Policy Learning for Multi-UAV Collision Avoidance with Causal Feature Selection.
CoRR, 2024

Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights.
CoRR, 2024

Learning Discrete Latent Variable Structures with Tensor Rank Conditions.
CoRR, 2024

S<sup>2</sup>GSL: Incorporating Segment to Syntactic Enhanced Graph Structure Learning for Aspect-based Sentiment Analysis.
CoRR, 2024

From Orthogonality to Dependency: Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals.
CoRR, 2024

On the Identification of Temporally Causal Representation with Instantaneous Dependence.
CoRR, 2024

Debiased Model-based Interactive Recommendation.
CoRR, 2024

When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting.
CoRR, 2024

Unifying Invariance and Spuriousity for Graph Out-of-Distribution via Probability of Necessity and Sufficiency.
CoRR, 2024

Learning by Doing: An Online Causal Reinforcement Learning Framework with Causal-Aware Policy.
CoRR, 2024

Granger causal representation learning for groups of time series.
Sci. China Inf. Sci., 2024

Combinatorial Routing for Neural Trees.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Individual Causal Structure Learning from Population Data.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Reducing Balancing Error for Causal Inference via Optimal Transport.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Automating the Selection of Proxy Variables of Unmeasured Confounders.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

From Large to Tiny: Distilling and Refining Mathematical Expertise for Math Word Problems with Weakly Supervision.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

S²GSL: Incorporating Segment to Syntactic Enhanced Graph Structure Learning for Aspect-based Sentiment Analysis.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Exploiting Geometry for Treatment Effect Estimation via Optimal Transport.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

An Optimal Transport View for Subspace Clustering and Spectral Clustering.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Multi-task ordinal regression with labeled and unlabeled data.
Inf. Sci., November, 2023

A selection-pattern-aware recommendation model with colored-motif attention network.
Neurocomputing, June, 2023

Nonlinear Causal Discovery for High-Dimensional Deterministic Data.
IEEE Trans. Neural Networks Learn. Syst., May, 2023

Learning dynamic causal mechanisms from non-stationary data.
Appl. Intell., March, 2023

Factorizing time-heterogeneous Markov transition for temporal recommendation.
Neural Networks, February, 2023

FFFN: Frame-By-Frame Feedback Fusion Network for Video Super-Resolution.
IEEE Trans. Multim., 2023

Identifying Semantic Component for Robust Molecular Property Prediction.
CoRR, 2023

A Survey on Causal Reinforcement Learning.
CoRR, 2023

Subspace Identification for Multi-Source Domain Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Some General Identification Results for Linear Latent Hierarchical Causal Structure.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Latent Causal Dynamics Model for Model-Based Reinforcement Learning.
Proceedings of the Neural Information Processing - 30th International Conference, 2023

Causal Discovery with Latent Confounders Based on Higher-Order Cumulants.
Proceedings of the International Conference on Machine Learning, 2023

Generalization Bound for Estimating Causal Effects from Observational Network Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Causal Discovery in Linear Non-Gaussian Acyclic Model With Multiple Latent Confounders.
IEEE Trans. Neural Networks Learn. Syst., 2022

Causal discovery from multi-domain data using the independence of modularities.
Neural Comput. Appl., 2022

Motif-based memory networks for complex-factoid question answering.
Neurocomputing, 2022

Learning granger causality for non-stationary Hawkes processes.
Neurocomputing, 2022

Shared state space model for background information extraction and time series prediction.
Neurocomputing, 2022

Double embedding-transfer-based multi-view spectral clustering.
Expert Syst. Appl., 2022

On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach.
CoRR, 2022

Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance.
CoRR, 2022

REST: Debiased Social Recommendation via Reconstructing Exposure Strategies.
CoRR, 2022

Causal Alignment Based Fault Root Causes Localization for Wireless Network.
Proceedings of the IEEE International Conference on Acoustics, 2022

Identification of Linear Latent Variable Model with Arbitrary Distribution.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Prediction of Synthetic Lethal Interactions in Human Cancers Using Multi-View Graph Auto-Encoder.
IEEE J. Biomed. Health Informatics, 2021

Causal Discovery with Confounding Cascade Nonlinear Additive Noise Models.
ACM Trans. Intell. Syst. Technol., 2021

Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems.
ACM Trans. Intell. Syst. Technol., 2021

Semi-supervised disentangled framework for transferable named entity recognition.
Neural Networks, 2021

Investigating the interpretability of fetal status assessment using antepartum cardiotocographic records.
BMC Medical Informatics Decis. Mak., 2021

Compensating the vorticity loss during advection with an adaptive vorticity confinement force.
Comput. Animat. Virtual Worlds, 2021

Learning causal structures using hidden compact representation.
Neurocomputing, 2021

CCSL: A Causal Structure Learning Method from Multiple Unknown Environments.
CoRR, 2021

TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations.
CoRR, 2021

Transferable Time-Series Forecasting under Causal Conditional Shift.
CoRR, 2021

On the Role of Entropy-based Loss for Learning Causal Structures with Continuous Optimization.
CoRR, 2021

THP: Topological Hawkes Processes for Learning Granger Causality on Event Sequences.
CoRR, 2021

FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders.
CoRR, 2021

Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Causal Discovery with Multi-Domain LiNGAM for Latent Factors.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Appearance-Motion Memory Consistency Network for Video Anomaly Detection.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Time Series Domain Adaptation via Sparse Associative Structure Alignment.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
An Efficient Entropy-Based Causal Discovery Method for Linear Structural Equation Models With IID Noise Variables.
IEEE Trans. Neural Networks Learn. Syst., 2020

DACH: Domain Adaptation Without Domain Information.
IEEE Trans. Neural Networks Learn. Syst., 2020

A causal discovery algorithm based on the prior selection of leaf nodes.
Neural Networks, 2020

Multi-context aware user-item embedding for recommendation.
Neural Networks, 2020

FOM: Fourth-order moment based causal direction identification on the heteroscedastic data.
Neural Networks, 2020

Mining hidden non-redundant causal relationships in online social networks.
Neural Comput. Appl., 2020

Animating turbulent fluid with a robust and efficient high-order advection method.
Comput. Animat. Virtual Worlds, 2020

Block diagonal representation learning for robust subspace clustering.
Inf. Sci., 2020

Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs.
CoRR, 2020

Detail-preserving smoke simulation using an efficient high-order numerical scheme.
Sci. China Inf. Sci., 2020

Dual-dropout graph convolutional network for predicting synthetic lethality in human cancers.
Bioinform., 2020

Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Meta Multi-Task Learning for Speech Emotion Recognition.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

DRS+: Load Shedding Meets Resource Auto-Scaling in Distributed Stream Processing.
Proceedings of the 22nd IEEE International Conference on High Performance Computing and Communications; 18th IEEE International Conference on Smart City; 6th IEEE International Conference on Data Science and Systems, 2020

TAG : Type Auxiliary Guiding for Code Comment Generation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Auto-scaling for real-time stream analytics on HPC cloud.
Serv. Oriented Comput. Appl., 2019

A subgraph-representation-based method for answering complex questions over knowledge bases.
Neural Networks, 2019

基于嵌入学习的用户动态偏好预测 (Predicting User's Dynamic Preference Based on Embedding Learning).
计算机科学, 2019

Disentanglement Challenge: From Regularization to Reconstruction.
CoRR, 2019

Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems.
CoRR, 2019

Causal Discovery with Cascade Nonlinear Additive Noise Models.
CoRR, 2019

NADAQ: Natural Language Database Querying Based on Deep Learning.
IEEE Access, 2019

Embedding Logic Rules Into Recurrent Neural Networks.
IEEE Access, 2019

Triad Constraints for Learning Causal Structure of Latent Variables.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Causal Discovery of Linear Non-Gaussian Acyclic Model with Small Samples.
Proceedings of the Intelligence Science and Big Data Engineering. Big Data and Machine Learning, 2019

Causal Discovery with Cascade Nonlinear Additive Noise Model.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Learning Disentangled Semantic Representation for Domain Adaptation.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
Sophisticated Merging Over Random Partitions: A Scalable and Robust Causal Discovery Approach.
IEEE Trans. Neural Networks Learn. Syst., 2018

Single image deraining using deep convolutional networks.
Multim. Tools Appl., 2018

A component-driven distributed framework for real-time video dehazing.
Multim. Tools Appl., 2018

Synthetic fluid details for the vorticity loss in advection.
Comput. Animat. Virtual Worlds, 2018

基于多视角多标签学习的读者情绪分类 (Emotion Classification for Readers Based on Multi-view Multi-label Learning).
计算机科学, 2018

Resource-Aware Stream Processing in High Performance Cloud Environment.
Proceedings of the 2018 IEEE SmartWorld, 2018

Causal Discovery from Discrete Data using Hidden Compact Representation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An Encoder-Decoder Framework Translating Natural Language to Database Queries.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

HPC2-ARS: An Architecture for Real-Time Analytic of Big Data Streams.
Proceedings of the 2018 IEEE International Conference on Web Services, 2018

Identification of Causality Among Gene Mutations Through Local Causal Association Rule Discovery.
Proceedings of the Neural Information Processing - 25th International Conference, 2018

Waterwheel: Realtime Indexing and Temporal Range Query Processing over Massive Data Streams.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Generating Natural Answers on Knowledge Bases and Text by Sequence-to-Sequence Learning.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

HASS: High Accuracy Spike Sorting with Wavelet Package Decomposition and Mutual Information.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

SELF: Structural Equational Likelihood Framework for Causal Discovery.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Understanding Social Causalities Behind Human Action Sequences.
IEEE Trans. Neural Networks Learn. Syst., 2017

DITIR: Distributed Index for High Throughput Trajectory Insertion and Real-time Temporal Range Query.
Proc. VLDB Endow., 2017

SBV: 基于SVG的生物信息可视化软件 (SBV: A Bioinformatics Visualization Software Based on SVG).
计算机科学, 2017

Recognizing activities from partially observed streams using posterior regularized conditional random fields.
Neurocomputing, 2017

An Encoder-Decoder Framework Translating Natural Language to Database Queries.
CoRR, 2017

SADA: A General Framework to Support Robust Causation Discovery with Theoretical Guarantee.
CoRR, 2017

Identification of adverse drug-drug interactions through causal association rule discovery from spontaneous adverse event reports.
Artif. Intell. Medicine, 2017

An efficient kurtosis-based causal discovery method for linear non-Gaussian acyclic data.
Proceedings of the 25th IEEE/ACM International Symposium on Quality of Service, 2017

A Robust Noise Resistant Algorithm for POI Identification from Flickr Data.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

An CNN-LSTM Attention Approach to Understanding User Query Intent from Online Health Communities.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

Component-Based Distributed Framework for Coherent and Real-Time Video Dehazing.
Proceedings of the 2017 IEEE International Conference on Computational Science and Engineering, 2017

A Dynamic Conditional Random Field Based Framework for Sentence-Level Sentiment Analysis of Chinese Microblog.
Proceedings of the 2017 IEEE International Conference on Computational Science and Engineering, 2017

2016
Multiple-cause discovery combined with structure learning for high-dimensional discrete data and application to stock prediction.
Soft Comput., 2016

Multi-Domain Manifold Learning for Drug-Target Interaction Prediction.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Sentiment Target Extraction Based on CRFs with Multi-features for Chinese Microblog.
Proceedings of the Web Technologies and Applications, 2016

2015
An improved clustering ensemble method based link analysis.
World Wide Web, 2015

Enhanced soft subspace clustering through hybrid dissimilarity.
J. Intell. Fuzzy Syst., 2015

Deterministic identification of specific individuals from GWAS results.
Bioinform., 2015

Causal discovery on high dimensional data.
Appl. Intell., 2015

Mining the Discriminative Word Sets for Bag-of-Words Model Based on Distributional Similarity Graph.
Proceedings of the Web Technologies and Applications, 2015

A Semi-supervised Solution for Cold Start Issue on Recommender Systems.
Proceedings of the Web Technologies and Applications - 17th Asia-PacificWeb Conference, 2015

2014
Determining molecular predictors of adverse drug reactions with causality analysis based on structure learning.
J. Am. Medical Informatics Assoc., 2014

A general framework of hierarchical clustering and its applications.
Inf. Sci., 2014

A Causal Model for Disease Pathway Discovery.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

2013
Causal gene identification using combinatorial V-structure search.
Neural Networks, 2013

Two novel interestingness measures for gene association rule mining.
Neural Comput. Appl., 2013

Product named entity recognition for Chinese query questions based on a skip-chain CRF model.
Neural Comput. Appl., 2013

Software project risk analysis using Bayesian networks with causality constraints.
Decis. Support Syst., 2013

Regularized Gaussian Mixture Model based discretization for gene expression data association mining.
Appl. Intell., 2013

An improved local adaptive clustering ensemble based on link analysis.
Proceedings of the International Conference on Machine Learning and Cybernetics, 2013

SADA: A General Framework to Support Robust Causation Discovery.
Proceedings of the 30th International Conference on Machine Learning, 2013

A Hybrid Approach for Large Scale Causality Discovery.
Proceedings of the Emerging Intelligent Computing Technology and Applications, 2013

Chinese Sentiment Classification Based on the Sentiment Drop Point.
Proceedings of the Emerging Intelligent Computing Technology and Applications, 2013

2012
Alpha Matting Using Artificial Immune Network.
Proceedings of the Advances in Swarm Intelligence - Third International Conference, 2012

Gaussian process learning for image classification based on low-level features.
Proceedings of the Eighth International Conference on Natural Computation, 2012

A cancer classification method based on association rules.
Proceedings of the 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012

Word similarity-based Schema Matching and its application in Chinese mobile phone information integration.
Proceedings of the 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012

2011
What is Unequal among the Equals? Ranking Equivalent Rules from Gene Expression Data.
IEEE Trans. Knowl. Data Eng., 2011

BASSUM: A Bayesian semi-supervised method for classification feature selection.
Pattern Recognit., 2011

A new hybrid method for gene selection.
Pattern Anal. Appl., 2011

2010
Portfolio adjusting optimization under credibility measures.
J. Comput. Appl. Math., 2010

Kernel based gene expression pattern discovery and its application on cancer classification.
Neurocomputing, 2010

2009
An efficient gene selection algorithm based on mutual information.
Neurocomputing, 2009

Kernel-based skyline cardinality estimation.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2009

2007
A Novel Gene Ranking Algorithm Based on Random Subspace Method.
Proceedings of the International Joint Conference on Neural Networks, 2007

An ACO Algorithm with Adaptive Volatility Rate of Pheromone Trail.
Proceedings of the Computational Science - ICCS 2007, 7th International Conference, Beijing, China, May 27, 2007

2006
A Novel ACO Algorithm with Adaptive Parameter.
Proceedings of the Computational Intelligence and Bioinformatics, 2006


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