Kun Zhang
Orcid: 0000-0002-0738-9958Affiliations:
- Carnegie Mellon University, Department of Philosophy, Pittsburgh, PA, USA
- Max Planck Institute for Intelligent Systems, Tübingen, Germany
- Chinese University of Hong Kong, Hong Kong (PhD 2005)
According to our database1,
Kun Zhang
authored at least 288 papers
between 2003 and 2024.
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Bibliography
2024
IEEE Trans. Neural Networks Learn. Syst., July, 2024
IEEE Trans. Knowl. Data Eng., July, 2024
IEEE Transactions on Neural Networks and Learning Systems Special Issue on Causal Discovery and Causality-Inspired Machine Learning.
IEEE Trans. Neural Networks Learn. Syst., April, 2024
ACM Trans. Knowl. Discov. Data, April, 2024
IEEE Trans. Pattern Anal. Mach. Intell., April, 2024
Delving Into Important Samples of Semi-Supervised Old Photo Restoration: A New Dataset and Method.
IEEE Trans. Multim., 2024
Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations.
J. Mach. Learn. Res., 2024
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables.
J. Mach. Learn. Res., 2024
CoRR, 2024
CoRR, 2024
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression.
CoRR, 2024
CoRR, 2024
CoRR, 2024
Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insight.
CoRR, 2024
Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges.
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
CoRR, 2024
A Randomized Controlled Trial on Anonymizing Reviewers to Each Other in Peer Review Discussions.
CoRR, 2024
When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting.
CoRR, 2024
Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models.
CoRR, 2024
Revealing Multimodal Contrastive Representation Learning through Latent Partial Causal Models.
CoRR, 2024
Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models.
CoRR, 2024
CoRR, 2024
On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors.
CoRR, 2024
CAAI Trans. Intell. Technol., 2024
MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification.
Proceedings of the ACM on Web Conference 2024, 2024
Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome.
Proceedings of the Persuasive Technology - 19th International Conference, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Causal Learning and Reasoning, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation.
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
IEEE Trans. Circuits Syst. Video Technol., October, 2023
Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions.
Neurocomputing, March, 2023
Model-Based Transfer Reinforcement Learning Based on Graphical Model Representations.
IEEE Trans. Neural Networks Learn. Syst., February, 2023
ACM Trans. Knowl. Discov. Data, 2023
IEEE J. Sel. Areas Inf. Theory, 2023
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective.
ACM Comput. Surv., 2023
How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation.
CoRR, 2023
CoRR, 2023
CoRR, 2023
Understanding Breast Cancer Survival: Using Causality and Language Models on Multi-omics Data.
CoRR, 2023
CoRR, 2023
Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data.
CoRR, 2023
Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the Conference on Causal Learning and Reasoning, 2023
Proceedings of the Conference on Causal Learning and Reasoning, 2023
2022
Causal Discovery in Linear Non-Gaussian Acyclic Model With Multiple Latent Confounders.
IEEE Trans. Neural Networks Learn. Syst., 2022
Entropy, 2022
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Action-Sufficient State Representation Learning for Control with Structural Constraints.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract).
Proceedings of the IEEE International Conference on Big Data, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Residual Similarity Based Conditional Independence Test and Its Application in Causal Discovery.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
IEEE Trans. Mob. Comput., 2021
ACM Trans. Intell. Syst. Technol., 2021
Neural Networks, 2021
CoRR, 2021
Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations.
CoRR, 2021
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
J. Real Time Image Process., 2020
J. Mach. Learn. Res., 2020
CoRR, 2020
Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs.
CoRR, 2020
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 2020 KDD Workshop on Causal Discovery (CD@KDD 2020), 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the Computer Vision - ECCV 2020, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
ACM Trans. Intell. Syst. Technol., 2019
Tracing the Propagation Path: A Flow Perspective of Representation Learning on Graphs.
CoRR, 2019
CoRR, 2019
Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach.
CoRR, 2019
Diagnosis of Autism Spectrum Disorder by Causal Influence Strength Learned from Resting-State fMRI Data.
CoRR, 2019
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 2019 ACM SIGKDD Workshop on Causal Discovery, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models.
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
Int. J. Data Sci. Anal., 2018
CoRR, 2018
CoRR, 2018
Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
Proceedings of 2018 ACM SIGKDD Workshop on Causal Discovery, 2018
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Proceedings of the Computer Vision - ECCV 2018, 2018
Collaborative Filtering With Social Exposure: A Modular Approach to Social Recommendation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
CoRR, 2017
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017
Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, 2017
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
On Estimation of Functional Causal Models: General Results and Application to the Post-Nonlinear Causal Model.
ACM Trans. Intell. Syst. Technol., 2016
ACM Trans. Intell. Syst. Technol., 2016
On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components.
Proceedings of the 32nd International Conference on Machine Learning, 2015
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2014
Neural Comput., 2014
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014
2013
CoRR, 2013
Proceedings of the 30th International Conference on Machine Learning, 2013
On Estimation of Functional Causal Models: Post-Nonlinear Causal Model as an Example.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013
2012
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
Proceedings of the 29th International Conference on Machine Learning, 2012
2011
Proceedings of the 3rd Asian Conference on Machine Learning, 2011
Proceedings of the UAI 2011, 2011
Proceedings of the UAI 2011, 2011
2010
Proceedings of the Causality: Objectives and Assessment (NIPS 2008 Workshop), 2010
J. Mach. Learn. Res., 2010
Convolutive blind source separation by efficient blind deconvolution and minimal filter distortion.
Neurocomputing, 2010
Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery.
Proceedings of the UAI 2010, 2010
Proceedings of the UAI 2010, 2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010
2009
Proceedings of the UAI 2009, 2009
Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009
Proceedings of the Independent Component Analysis and Signal Separation, 2009
2007
IEEE Signal Process. Lett., 2007
Proceedings of the Intelligent Data Engineering and Automated Learning, 2007
Proceedings of the Machine Learning, 2007
Proceedings of the Independent Component Analysis and Signal Separation, 2007
2006
IEEE Trans. Pattern Anal. Mach. Intell., 2006
Proceedings of the Intelligent Data Engineering and Automated Learning, 2006
Proceedings of the Neural Information Processing, 13th International Conference, 2006
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006
2005
Neural Comput., 2005
Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005
2003
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003