Posts by Collection

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Multivariate Scoring Functions

Published in , 2020

• Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank
  Tao Yang, Shikai Fang, Shibo Li, Yulan Wang, Qingyao Ai
  Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020)
  Paper | Video

Online Bayesian Sparse Learning

Published in , 2020

• Online Bayesian Sparse Learning with Spike and Slab Priors
  Shikai Fang, Shandian Zhe, Kuang-chih Lee, Kai Zhang, Jennifer Neville
  IEEE International Conference on Data Mining (ICDM 2020)
  Paper | Code | Slides

Probabilistic Neural Kernel Tensor

Published in , 2020

• Probabilistic Neural-Kernel Tensor Decomposition
  Conor Tillinghast, Shikai Fang, Kai Zhang, Shandian Zhe
  IEEE International Conference on Data Mining (ICDM 2020)
  Paper | Code | Slides

Bayesian Streaming Sparse Tucker

Published in , 2021

• Bayesian Streaming Sparse Tucker Decomposition
  Shikai Fang, Robert. M. Kirby, Shandian Zhe
  The 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021)
  Paper | Code | Slides | Supp

Streaming Bayesian Deep Tensor

Published in , 2021

• Streaming Bayesian Deep Tensor Factorization
  Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe
  The 38th International Conference on Machine Learning (ICML 2021)
  Paper | Code | Supp | Video | Slides

Bayesian Continuous Time Tucker

Published in , 2022

• Bayesian Continuous-Time Tucker Decomposition
  Shikai Fang, Akil Narayan, Robert Kirby, Shandian Zhe
  The 39th International Conference on Machine Learning (ICML 2022) [Oral (top 2%)]
  Paper | Code | Slides | Poster | Video

Schrodinger Bridge

Published in , 2023

• Provably Convergent Schrodinger Bridge with Applications to Probabilistic Time Series Imputation
  Yu Chen^*, Wei Deng^*, Shikai Fang^*, Fengpei Li^*, Tianjiao Nicole Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
  The 40th International Conference on Machine Learning (ICML 2023)
  Paper | Code

Multi Omic Integration

Published in , 2023

• Multi-Omic Integration of Blood-Based Tumor Associated Genomic And Lipidomic Profiles Using Machine Learning Models in Metastatic Prostate Cancer
  Shikai Fang, Shandian Zhe, Hui-Ming Lin, Arun A. Azad, Heidi Fettke, Edmond M Kwan, Lisa Horvath, Blossom Mak, Tiantian Zheng, Pan Du, Shidong Jia, Robert M. Kirby, Manish Kohli MD
  JCO Clinical Cancer Informatics (JCO CCI) [most read paper on JCO CCI!]
  Paper | PDF | Supp

Dynamic Tensor Decomposition

Published in , 2023

• Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes
  Zheng Wang^*, Shikai Fang^*, Shibo Li, Shandian Zhe
  The 37th Conference on Neural Information Processing Systems (NeurIPS 2023) [Spotlight! (top 10%)]
  Paper | Code | Poster

Streaming Factor Trajectory

Published in , 2023

• Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
  Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Robert Kirby, Shandian Zhe
  The 37th Conference on Neural Information Processing Systems (NeurIPS 2023)
  Paper | Code | Poster | Slides

Functional Bayesian Tucker

Published in , 2024

• Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor
  Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe
  The 12th International Conference on Learning Representations (ICLR 2024)
  Paper | Code | Poster | Slides

Gaussian Process Pde

Published in , 2024

• Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
  Shikai Fang^*, Madison Cooley^*, Da Long^*, Shibo Li, Robert Kirby, Shandian Zhe
  The 12th International Conference on Learning Representations (ICLR 2024)
  Paper | Code | Poster | Slides

Bayotide

Published in , 2024

• BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition
  Shikai Fang, Qingsong Wen, Yingtao Luo, Shandian Zhe, Liang Sun
  The 41st International Conference on Machine Learning (ICML 2024)[Spotlight! (top 3%)]
  Paper | Code | Slides

Mars

Published in , 2025

• MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
  Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
  The 13th International Conference on Learning Representations (ICLR 2025)
  Arxiv | Code | Website

Sound Speed Sr Diffusion

Published in , 2025

• Hybrid data-and model-driven three-dimensional ocean sound speed field super-resolution: Diffusion model meets low-rank tensor
  Yifan Sun, Siyuan Li, Shikai Fang, Lei Cheng, Jianlong Li, Peter Gerstoft
  The Journal of the Acoustical Society of America (JASA)
  Paper | Code

Phy Guidied Weather Downscaling

Published in , 2025

• Physics-Guided Learning of Meteorological Dynamics for Weather Forecasting and Downscaling
  Yingtao Luo, Shikai Fang, Binqing Wu, Qingsong Wen, Liang Sun
  2025 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2025)
  Arxiv | Code

Far Ts

Published in , 2025

• Less Is More: Generating Time Series with LLaMA-Style Autoregression in Simple Factorized Latent Spaces
  Siyuan Li, Yifan Sun, Lei Cheng, Lewen Wang, Yang Liu, Weiqing Liu, Jianlong Li, Jiang Bian, Shikai Fang†
  Arxiv

Rdagent

Published in , 2025

• R&D-Agent: Automating Data-Driven AI Solution Building Through LLM-Powered Automated Research, Development, and Evolution
  Xu Yang^*, Xiao Yang^*,Shikai Fang, Bowen Xian, Yuante Li, Jian Wang, Minrui Xu, Haoran Pan, Xinpeng Hong, Weiqing Liu, Yelong Shen, Weizhu Chen, Jiang Bian
  Arxiv | Code | Best MLE agent verified by OpenAI-MLE-Bench!

Catte Tensor

Published in , 2025

• CATTE :Functional Complexity-adaptive Temporal Tensor Decomposition
  Panqi Chen, Lei Cheng†, Jianlong Li, Weichang Li, Weiqing Liu, Jiang Bian, Shikai Fang†
  The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)
  Arxiv | Code

Sdift Diffusion

Published in , 2025

• Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
  Panqi Chen, Yifan Sun, Lei Cheng†, Yang Yang, Weichang Li, Yang Liu, Weiqing Liu, Jiang Bian, Shikai Fang†
  The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)
  Arxiv | Code

Bayestensor Mogp

Published in , 2025

• When Bayesian Tensor Completion Meets Multioutput Gaussian Processes: Functional Universality and Rank Learning
  Siyuan Li, Shikai Fang, Lei Cheng, Feng Yin, Yik-Chung Wu, Peter Gerstoft, Sergios Theodoridis
  IEEE Transactions on Signal Processing (TSP)
  Arxiv | Code

Graph Gp Ts

Published in , 2026

• Irregular Multivariate Time Series Modeling Via Latent Graph-Guided Gaussian Process Priors
  Siyuan Li, Shikai Fang, Lei Cheng, Alexandre Thiery, Sergios Theodoridis
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2026)
  Arxiv

Bayesian Learning for High Order Data

Research roadmap and insights for Bayesian learning approaches in high-dimensional tensor data analysis

Tensor Learning for Real-World Structural Data

The high-order & low-rank essence of real-world data, compact representations for structural data, and the frontier of generative AI

真实世界结构数据的张量学习

真实世界数据的高阶与低秩本质，结构数据的紧凑表征，以及生成式AI的前沿探索

Bayesian Continuous-Time Tucker Decomposition

Published: July 01, 2022

Presentation on continuous-time Bayesian tensor decomposition for streaming tensor-valued time series.

Streaming Factor Trajectory Learning for Temporal Tensor Decomposition

Published: December 01, 2023

Presentation on online trajectory learning for temporal tensor decomposition in streaming settings.

Solving High Frequency and Multi-Scale PDEs with Gaussian Processes

Published: May 01, 2024

Presentation on Gaussian process surrogates for high-frequency and multi-scale PDE systems.

BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition

Published: July 01, 2024

Presentation on Bayesian online imputation for continuous-indexed multivariate time series.

The Application of Gaussian Processes in Time Series and PDE-solving

Published: September 01, 2025

Invited academic talk on the application of Gaussian processes in time series modeling and PDE solving.

Towards Intelligence Driven by Physical-World Signals

Published: October 01, 2025

Invited industry talk on intelligence driven by physical-world signals and AI for signal processing.

AI for Science: Foundation Models, Agents, and Scientific Discovery

Published: November 01, 2025

Invited talk on AI for science, with a focus on foundation models and agentic systems for scientific modeling and discovery.

LLM-based Auto-evolving Agents for Data-driven R&D

Published: April 01, 2026

Invited online talk on LLM-based auto-evolving agents for data-driven R&D.

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.