Naiqi Li

According to our database, Naiqi Li authored at least 23 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Node-Level Graph Regression With Deep Gaussian Process Models.

Naiqi Li, Wenjie Li, Yinghua Gao, Yiming Li, Jigang Bao, Ercan E. Kuruoglu, Yong Jiang, Shu-Tao Xia

IEEE Trans. Artif. Intell., June, 2024

Portfolio Selection via Graph-Aware Gaussian Processes With Generalized Gaussian Likelihood.

Naiqi Li, Zhikang Xia, Yiming Li, Ercan E. Kuruoglu, Yong Jiang, Shu-Tao Xia

IEEE Trans. Artif. Intell., February, 2024

Generative Pre-Trained Diffusion Paradigm for Zero-Shot Time Series Forecasting.

Jiarui Yang, Tao Dai, Naiqi Li, Junxi Wu, Peiyuan Liu, Jinmin Li, Jigang Bao, Haigang Zhang, Shutao Xia

CoRR, 2024

LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling.

Yaohua Zha, Naiqi Li, Yanzi Wang, Tao Dai, Hang Guo, Bin Chen, Zhi Wang, Zhihao Ouyang, Shu-Tao Xia

CoRR, 2024

Taming Pre-trained LLMs for Generalised Time Series Forecasting via Cross-modal Knowledge Distillation.

Peiyuan Liu, Hang Guo, Tao Dai, Naiqi Li, Jigang Bao, Xudong Ren, Yong Jiang, Shu-Tao Xia

CoRR, 2024

MB-RACS: Measurement-Bounds-based Rate-Adaptive Image Compressed Sensing Network.

Yujun Huang, Bin Chen, Naiqi Li, Baoyi An, Shu-Tao Xia, Yaowei Wang

CoRR, 2024

GladCoder: Stylized QR Code Generation with Grayscale-Aware Denoising Process.

Yuqiu Xie, Bolin Jiang, Jiawei Li, Naiqi Li, Bin Chen, Tao Dai, Yuang Peng, Shu-Tao Xia

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Periodicity Decoupling Framework for Long-term Series Forecasting.

Tao Dai, Beiliang Wu, Peiyuan Liu, Naiqi Li, Jigang Bao, Yong Jiang, Shu-Tao Xia

Proceedings of the Twelfth International Conference on Learning Representations, 2024

WFTNet: Exploiting Global and Local Periodicity in Long-Term Time Series Forecasting.

Peiyuan Liu, Beiliang Wu, Naiqi Li, Tao Dai, Fengmao Lei, Jigang Bao, Yong Jiang, Shu-Tao Xia

Proceedings of the IEEE International Conference on Acoustics, 2024

CAGEN: Controllable Anomaly Generator using Diffusion Model.

Bolin Jiang, Yuqiu Xie, Jiawei Li, Naiqi Li, Yong Jiang, Shu-Tao Xia

Proceedings of the IEEE International Conference on Acoustics, 2024

Procedural Level Generation with Diffusion Models from a Single Example.

Shiqi Dai, Xuanyu Zhu, Naiqi Li, Tao Dai, Zhi Wang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model.

Xinyi Zhang, Naiqi Li, Jiawei Li, Tao Dai, Yong Jiang, Shu-Tao Xia

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Difficulty-Aware Data Augmentor for Scene Text Recognition.

Guanghao Meng, Tao Dai, Bin Chen, Naiqi Li, Yong Jiang, Shu-Tao Xia

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

SsaA: A Self-supervised auto-Annotation System for Online Visual Inspection and Manufacturing Automation.

Jiawei Li, Bolin Jiang, Yan Liu, Chengxiao Luo, Naiqi Li, Bin Chen

CoRR, 2022

Deep Dirichlet process mixture models.

Naiqi Li, Wenjie Li, Yong Jiang, Shu-Tao Xia

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

GDTW: A Novel Differentiable DTW Loss for Time Series Tasks.

Xiang Liu, Naiqi Li, Shu-Tao Xia

Proceedings of the IEEE International Conference on Acoustics, 2021

H-GPR: A Hybrid Strategy for Large-Scale Gaussian Process Regression.

Naiqi Li, Yinghua Gao, Wenjie Li, Yong Jiang, Shu-Tao Xia

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Stochastic Deep Gaussian Processes over Graphs.

Naiqi Li, Wenjie Li, Jifeng Sun, Yinghua Gao, Yong Jiang, Shu-Tao Xia

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalized Local Aggregation for Large Scale Gaussian Process Regression.

Yinghua Gao, Naiqi Li, Ning Ding, Yiming Li, Tao Dai, Shu-Tao Xia

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2016

Automatic Verification of Golog Programs via Predicate Abstraction.

Peiming Mo, Naiqi Li, Yongmei Liu

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015

Automatic Verification of Partial Correctness of Golog Programs.

Naiqi Li, Yongmei Liu

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2013

Reasoning about State Constraints in the Situation Calculus.

Naiqi Li, Yi Fan, Yongmei Liu

Proceedings of the IJCAI 2013, 2013

2012

A First-Order Interpreter for Knowledge-Based Golog with Sensing based on Exact Progression and Limited Reasoning.

Yi Fan, Minghui Cai, Naiqi Li, Yongmei Liu

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012