no code implementations • 6 Apr 2024 • Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu, Lina Yao
Such a failure may overlook the conditionality between two domains and how it contributes to latent factor disentanglement, leading to negative transfer when domains are weakly correlated.
no code implementations • 4 Sep 2023 • Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu, Lina Yao
Next, we aim to build distributional implicit matchings between the domain-level preferences of two domains.
no code implementations • 23 Mar 2023 • Zesheng Ye, Jing Du, Lina Yao
Conditional Neural Processes~(CNPs) formulate distributions over functions and generate function observations with exact conditional likelihoods.
no code implementations • 15 Mar 2023 • Yao Liu, Zesheng Ye, Rui Wang, Binghao Li, Quan Z. Sheng, Lina Yao
Tremendous efforts have been put forth on predicting pedestrian trajectory with generative models to accommodate uncertainty and multi-modality in human behaviors.
no code implementations • 9 Aug 2022 • Jing Du, Zesheng Ye, Lina Yao, Bin Guo, Zhiwen Yu
In this study, we address these concerns by learning (1) multi-scale representations of short-term interests; and (2) dynamics-aware representations of long-term interests.
no code implementations • 7 Aug 2022 • Zesheng Ye, Lina Yao, Yu Zhang, Sylvia Gustin
Recent studies demonstrate the use of a two-stage supervised framework to generate images that depict human perception to visual stimuli from EEG, referring to EEG-visual reconstruction.
no code implementations • CVPR 2022 • Zesheng Ye, Lina Yao
Conditional Neural Processes~(CNPs) bridge neural networks with probabilistic inference to approximate functions of Stochastic Processes under meta-learning settings.