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2020 – today
- 2024
[j14]Zhuangyan Fang
, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He:
On Low-Rank Directed Acyclic Graphs and Causal Structure Learning. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4924-4937 (2024)- [c39]Junlong Lyu, Zhitang Chen, Shoubo Feng:
Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models. ICML 2024 - [i34]Tim Tse, Isaac Chan, Zhitang Chen:
Causal Coordinated Concurrent Reinforcement Learning. CoRR abs/2401.18012 (2024) - [i33]Tim Tse, Zhitang Chen, Shengyu Zhu, Yue Liu:
Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms. CoRR abs/2401.18017 (2024) - 2023
- [j13]Ran Chen, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Bei Yu, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao:
A Unified Framework for Layout Pattern Analysis With Deep Causal Estimation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(4): 1199-1211 (2023) - [j12]Siting Liu, Yuan Pu, Peiyu Liao, Hongzhong Wu, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu:
FastGR: Global Routing on CPU-GPU With Heterogeneous Task Graph Scheduler. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(7): 2317-2330 (2023) - [j11]Yunqi Wang, Furui Liu, Zhitang Chen, Yik-Chung Wu, Jianye Hao, Guangyong Chen, Pheng-Ann Heng:
Contrastive-ACE: Domain Generalization Through Alignment of Causal Mechanisms. IEEE Trans. Image Process. 32: 235-250 (2023) - [c38]Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng:
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. AAAI 2023: 14400-14407 - [c37]Kaiwen Zhou, Zhilin Chen, Guochen Liu, Zhitang Chen:
A Novel Extrapolation Technique to Accelerate WMMSE. ICASSP 2023: 1-5 - [c36]Siting Liu, Yuan Pu, Peiyu Liao, Hongzhong Wu, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu:
FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler (Extended Abstract). IJCAI 2023: 6458-6462 - [c35]Lin Yang, Junlong Lyu, Wenlong Lyu, Zhitang Chen:
Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs. NeurIPS 2023 - [i32]Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng:
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. CoRR abs/2301.03412 (2023) - [i31]Junlong Lyu, Zhitang Chen, Wenlong Lyu, Jianye Hao:
Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization. CoRR abs/2301.12640 (2023) - [i30]Wenlong Lyu, Shoubo Hu, Jie Chuai, Zhitang Chen:
Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets. CoRR abs/2308.04660 (2023) - [i29]Junlong Lyu, Zhitang Chen, Shoubo Feng:
Convergence guarantee for consistency models. CoRR abs/2308.11449 (2023) - [i28]Lin Yang, Junlong Lyu, Wenlong Lyu, Zhitang Chen:
Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs. CoRR abs/2310.20145 (2023) - 2022
- [j10]Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang:
Weakly Supervised Disentangled Generative Causal Representation Learning. J. Mach. Learn. Res. 23: 241:1-241:55 (2022) - [c34]Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu:
Out-of-distribution Generalization with Causal Invariant Transformations. CVPR 2022: 375-385 - [c33]Siting Liu, Peiyu Liao, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu:
FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler. DATE 2022: 760-765 - [c32]Peiyu Liao, Siting Liu, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu:
DREAMPlace 4.0: Timing-driven Global Placement with Momentum-based Net Weighting. DATE 2022: 939-944 - [c31]Chang Feng, Wenlong Lyu, Zhitang Chen, Junjie Ye, Mingxuan Yuan, Jianye Hao:
Batch Sequential Black-Box Optimization with Embedding Alignment Cells for Logic Synthesis. ICCAD 2022: 56:1-56:9 - [c30]Lin Yang, Min Cheng, Jun Qu, Zhitang Chen:
GraphHO: A Graph-based Handover Optimization System for Cellular Networks. ISWCS 2022: 1-6 - [c29]Xiaopeng Zhang, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Evangeline F. Y. Young, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao:
RCANet: Root Cause Analysis via Latent Variable Interaction Modeling for Yield Improvement. ITC 2022: 100-107 - [c28]Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Chen Yongwei:
Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates. NeurIPS 2022 - [c27]Ignavier Ng, Shengyu Zhu, Zhuangyan Fang, Haoyang Li, Zhitang Chen, Jun Wang:
Masked Gradient-Based Causal Structure Learning. SDM 2022: 424-432 - [c26]Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen:
Reframed GES with a neural conditional dependence measure. UAI 2022: 1782-1791 - [i27]Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Yongwei Chen:
Universality of parametric Coupling Flows over parametric diffeomorphisms. CoRR abs/2202.02906 (2022) - [i26]Mengyue Yang, Xinyu Cai, Furui Liu, Xu Chen, Zhitang Chen, Jianye Hao, Jun Wang:
Generalizable Information Theoretic Causal Representation. CoRR abs/2202.08388 (2022) - [i25]Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu:
Out-of-distribution Generalization with Causal Invariant Transformations. CoRR abs/2203.11528 (2022) - [i24]Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen:
Reframed GES with a Neural Conditional Dependence Measure. CoRR abs/2206.08531 (2022) - 2021
- [j9]Yang Li, Zhitang Chen, Guochen Liu, Yik-Chung Wu, Kai-Kit Wong:
Learning to Construct Nested Polar Codes: An Attention-Based Set-to-Element Model. IEEE Commun. Lett. 25(12): 3898-3902 (2021) - [j8]Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang:
Asymptotically Optimal One- and Two-Sample Testing With Kernels. IEEE Trans. Inf. Theory 67(4): 2074-2092 (2021) - [c25]Mengyue Yang, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, Jun Wang:
CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models. CVPR 2021: 9593-9602 - [c24]Ran Chen, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Bei Yu, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao:
A Unified Framework for Layout Pattern Analysis with Deep Causal Estimation. ICCAD 2021: 1-9 - [c23]Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang:
Ordering-Based Causal Discovery with Reinforcement Learning. IJCAI 2021: 3566-3573 - [i23]Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang:
Ordering-Based Causal Discovery with Reinforcement Learning. CoRR abs/2105.06631 (2021) - [i22]Yunqi Wang, Furui Liu, Zhitang Chen, Qing Lian, Shoubo Hu, Jianye Hao, Yik-Chung Wu:
Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms. CoRR abs/2106.00925 (2021) - [i21]Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander I. Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar:
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. CoRR abs/2106.03609 (2021) - [i20]Keli Zhang, Shengyu Zhu, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, Lujia Pan:
gCastle: A Python Toolbox for Causal Discovery. CoRR abs/2111.15155 (2021) - [i19]Xiangle Cheng, James He, Shihan Xiao, Yingxue Zhang, Zhitang Chen, Pascal Poupart, Fenglin Li:
Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks. CoRR abs/2112.12321 (2021) - 2020
- [j7]Haonan Duan, Abdullah Rashwan, Pascal Poupart, Zhitang Chen:
Discriminative training of feed-forward and recurrent sum-product networks by extended Baum-Welch. Int. J. Approx. Reason. 124: 66-81 (2020) - [c22]Shengyu Zhu, Ignavier Ng, Zhitang Chen:
Causal Discovery with Reinforcement Learning. ICLR 2020 - [c21]Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen:
Stable Learning via Differentiated Variable Decorrelation. KDD 2020: 2185-2193 - [i18]Mengyue Yang, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, Jun Wang:
CausalVAE: Structured Causal Disentanglement in Variational Autoencoder. CoRR abs/2004.08697 (2020) - [i17]Vahid Partovi Nia, Xinlin Li, Masoud Asgharian, Shoubo Hu, Zhitang Chen, Yanhui Geng:
Clustering Causal Additive Noise Models. CoRR abs/2006.04877 (2020) - [i16]Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He:
Low Rank Directed Acyclic Graphs and Causal Structure Learning. CoRR abs/2006.05691 (2020) - [i15]Yifei Wang, Dan Peng, Furui Liu, Zhenguo Li, Zhitang Chen, Jiansheng Yang:
Decoder-free Robustness Disentanglement without (Additional) Supervision. CoRR abs/2007.01356 (2020) - [i14]Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang:
Disentangled Generative Causal Representation Learning. CoRR abs/2010.02637 (2020) - [i13]Minne Li, Mengyue Yang, Furui Liu, Xu Chen, Zhitang Chen, Jun Wang:
Causal World Models by Unsupervised Deconfounding of Physical Dynamics. CoRR abs/2012.14228 (2020)
2010 – 2019
- 2019
- [j6]Zhitang Chen, Zhongpeng Wang, Kun Wang, Weibo Yi, Hongzhi Qi:
Recognizing Motor Imagery Between Hand and Forearm in the Same Limb in a Hybrid Brain Computer Interface Paradigm: An Online Study. IEEE Access 7: 59631-59639 (2019) - [j5]Shoubo Hu, Bogdan Cautis, Zhitang Chen, Laiwan Chan, Yanhui Geng, Xiuqiang He:
Model-free inference of diffusion networks using RKHS embeddings. Data Min. Knowl. Discov. 33(2): 499-525 (2019) - [c20]Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen:
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. AISTATS 2019: 1544-1553 - [c19]Xiaoxiao Wang, Xueying Guo, Jie Chuai, Zhitang Chen, Xin Liu:
Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration. IEEE BigData 2019: 1517-1526 - [c18]Jie Chuai, Zhitang Chen, Guochen Liu, Xueying Guo, Xiaoxiao Wang, Xin Liu, Chongming Zhu, Feiyi Shen:
A Collaborative Learning Based Approach for Parameter Configuration of Cellular Networks. INFOCOM 2019: 1396-1404 - [c17]Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan:
Domain Generalization via Multidomain Discriminant Analysis. UAI 2019: 292-302 - [i12]Shengyu Zhu, Zhitang Chen:
Causal Discovery with Reinforcement Learning. CoRR abs/1906.04477 (2019) - [i11]Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan:
Domain Generalization via Multidomain Discriminant Analysis. CoRR abs/1907.11216 (2019) - [i10]Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang:
Asymptotically Optimal One- and Two-Sample Testing with Kernels. CoRR abs/1908.10037 (2019) - [i9]Zhitang Chen, Shengyu Zhu, Yue Liu, Tim Tse:
Causal Discovery by Kernel Intrinsic Invariance Measure. CoRR abs/1909.00513 (2019) - [i8]Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen:
Masked Gradient-Based Causal Structure Learning. CoRR abs/1910.08527 (2019) - [i7]Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang:
A Graph Autoencoder Approach to Causal Structure Learning. CoRR abs/1911.07420 (2019) - 2018
- [j4]Xueying Guo, George Trimponias, Xiaoxiao Wang, Zhitang Chen, Yanhui Geng, Xin Liu:
Learning-Based Joint Configuration for Cellular Networks. IEEE Internet Things J. 5(6): 4283-4295 (2018) - [j3]Shoubo Hu, Zhitang Chen, Laiwan Chan:
A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference. Neural Comput. 30(5) (2018) - [c16]Zhuoshu Li, Zhitang Chen, Pascal Poupart, Sanmay Das, Yanhui Geng:
Faster Policy Adaptation in Environments with Exogeneity: A State Augmentation Approach. AAMAS 2018: 1035-1043 - [c15]Zhitang Chen, Xin Zhao, Zhongpeng Wang, Kun Wang, Weibo Yi, Feng He, Hongzhi Qi:
A Hybrid Brain Computer Interface Driven by Motor Imagery of Right Hand Versus Right Forearm. iCAST 2018: 79-83 - [c14]Thomas G. Dietterich, George Trimponias, Zhitang Chen:
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning. ICML 2018: 1261-1269 - [c13]Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Lai-Wan Chan, Yanhui Geng:
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models. NeurIPS 2018: 5212-5222 - [c12]Abdullah Rashwan, Pascal Poupart, Zhitang Chen:
Discriminative Training of Sum-Product Networks by Extended Baum-Welch. PGM 2018: 356-367 - [i6]Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen:
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. CoRR abs/1802.07581 (2018) - [i5]Shengyu Zhu, Biao Chen, Zhitang Chen:
Exponentially Consistent Kernel Two-Sample Tests. CoRR abs/1802.08407 (2018) - [i4]Thomas G. Dietterich, George Trimponias, Zhitang Chen:
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning. CoRR abs/1806.01584 (2018) - [i3]Shoubo Hu, Zhitang Chen, Laiwan Chan:
A Kernel Embedding-based Approach for Nonstationary Causal Model Inference. CoRR abs/1809.08560 (2018) - [i2]Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Laiwan Chan, Yanhui Geng:
Causal Inference and Mechanism Clustering of a Mixture of Additive Noise Models. CoRR abs/1809.08568 (2018) - [i1]Xiaoxiao Wang, Xueying Guo, Jie Chuai, Zhitang Chen, Xin Liu:
Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration. CoRR abs/1811.10902 (2018) - 2017
- [c11]Zhitang Chen, Ke He, Jian Li, Yanhui Geng:
Seq2Img: A sequence-to-image based approach towards IP traffic classification using convolutional neural networks. IEEE BigData 2017: 1271-1276 - [c10]Xueying Guo, George Trimponias, Xiaoxiao Wang, Zhitang Chen, Yanhui Geng, Xin Liu:
Cellular network configuration via online learning and joint optimization. IEEE BigData 2017: 1295-1300 - [c9]Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart:
Online Bayesian Transfer Learning for Sequential Data Modeling. ICLR (Poster) 2017 - 2016
- [c8]Zhitang Chen, Pascal Poupart, Yanhui Geng:
Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings. AISTATS 2016: 573-581 - [c7]Zhitang Chen, Jiayao Wen, Yanhui Geng:
Predicting future traffic using Hidden Markov Models. ICNP 2016: 1-6 - [c6]Pascal Poupart, Zhitang Chen, Priyank Jaini, Fred Fung, Hengky Susanto, Yanhui Geng, Li Chen, Kai Chen, Hao Jin:
Online flow size prediction for improved network routing. ICNP 2016: 1-6 - [c5]Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart:
Online Algorithms for Sum-Product Networks with Continuous Variables. Probabilistic Graphical Models 2016: 228-239 - 2014
- [j2]Zhitang Chen, Kun Zhang, Laiwan Chan, Bernhard Schölkopf:
Causal Discovery via Reproducing Kernel Hilbert Space Embeddings. Neural Comput. 26(7): 1484-1517 (2014) - 2013
- [j1]Zhitang Chen, Laiwan Chan:
Causality in Linear Nongaussian Acyclic Models in the Presence of Latent Gaussian Confounders. Neural Comput. 25(6): 1605-1641 (2013) - [c4]Zhitang Chen, Kun Zhang, Laiwan Chan:
Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method. ICDM 2013: 1003-1008 - 2012
- [c3]Zhitang Chen, Laiwan Chan:
Causal Discovery for Linear Non-Gaussian Acyclic Models in the Presence of Latent Gaussian Confounders. LVA/ICA 2012: 17-24 - [c2]Zhitang Chen, Kun Zhang, Laiwan Chan:
Causal discovery with scale-mixture model for spatiotemporal variance dependencies. NIPS 2012: 1736-1744 - 2011
- [c1]Zhitang Chen, Laiwan Chan:
New approaches for solving permutation indeterminacy and scaling ambiguity in frequency domain separation of convolved mixtures. IJCNN 2011: 911-918
Coauthor Index
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last updated on 2024-09-13 00:44 CEST by the dblp team
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