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Defu Cao

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Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning

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Apr 15, 2024
Xiongye Xiao, Gengshuo Liu, Gaurav Gupta, Defu Cao, Shixuan Li, Yaxing Li, Tianqing Fang, Mingxi Cheng, Paul Bogdan

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Exploring Neuron Interactions and Emergence in LLMs: From the Multifractal Analysis Perspective

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Feb 14, 2024
Xiongye Xiao, Chenyu Zhou, Heng Ping, Defu Cao, Yaxing Li, Yizhuo Zhou, Shixuan Li, Paul Bogdan

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Guiding Large Language Models with Divide-and-Conquer Program for Discerning Problem Solving

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Feb 08, 2024
Yizhou Zhang, Lun Du, Defu Cao, Qiang Fu, Yan Liu

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TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

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Oct 12, 2023
Defu Cao, Furong Jia, Sercan O Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu

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Neuro-Inspired Hierarchical Multimodal Learning

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Sep 27, 2023
Xiongye Xiao, Gengshuo Liu, Gaurav Gupta, Defu Cao, Shixuan Li, Yaxing Li, Tianqing Fang, Mingxi Cheng, Paul Bogdan

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Detecting Out-of-Context Multimodal Misinformation with interpretable neural-symbolic model

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Apr 15, 2023
Yizhou Zhang, Loc Trinh, Defu Cao, Zijun Cui, Yan Liu

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Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders

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Mar 04, 2023
Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu

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Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential Equations

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Mar 04, 2023
Xiongye Xiao, Defu Cao, Ruochen Yang, Gaurav Gupta, Gengshuo Liu, Chenzhong Yin, Radu Balan, Paul Bogdan

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Estimating Treatment Effects in Continuous Time with Hidden Confounders

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Feb 21, 2023
Defu Cao, James Enouen, Yan Liu

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DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift

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Nov 17, 2022
Defu Cao, Yousef El-Laham, Loc Trinh, Svitlana Vyetrenko, Yan Liu

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