Publications (27)
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion
Xing Han, Huy Nguyen, Carl Harris +2
As machine learning models in critical fields increasingly grapple with multimodal data, they face the dual challenges of handling a wide array of modalities, often incomplete due…
LSTTN: A Long-Short Term Transformer-based Spatio-temporal Neural Network for Traffic Flow Forecasting
Qinyao Luo, Silu He, Xing Han +2
Accurate traffic forecasting is a fundamental problem in intelligent transportation systems and learning long-range traffic representations with key information through spatiotempo…
MILM: Large Language Models for Multimodal Irregular Time Series with Informative Sampling
Hsing-Huan Chung, Shijun Li, Yoav Wald +3
Multimodal irregular time series (MITS) consist of asynchronous and irregularly sampled observations from heterogeneous numerical and textual channels. In healthcare, for example,…
Non-reciprocal Cavity Polariton with Atoms Strongly Coupled to Optical Cavity
Pengfei Yang, Ming Li, Xing Han +6
Breaking the time-reversal symmetry of light is of great importance for fundamental physics and has attracted increasing interest in the study of non-reciprocal photonic devices. H…
Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series
Xing Han, Sambarta Dasgupta, Joydeep Ghosh
Many real-life applications involve simultaneously forecasting multiple time series that are hierarchically related via aggregation or disaggregation operations. For instance, comm…
Novel Node Category Detection Under Subpopulation Shift
Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald +2
In real-world graph data, distribution shifts can manifest in various ways, such as the emergence of new categories and changes in the relative proportions of existing categories.…