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Cen-You Li

2 accepted papers

2026

Efficient Autoregressive Inference for Transformer Probabilistic Models

ICLR 2026poster

Transformer-based models for amortized probabilistic inference, such as neural processes, prior-fitted networks, and tabular foundation models, excel at single-pass *marginal* prediction. However, many real-world applications require coherent *joint distributions* that capture dependencies between p…

Cited by 0SourceScholar
2022

Safe Active Learning for Multi-Output Gaussian Processes

AISTATS 2022poster

Multi-output regression problems are commonly encountered in science and engineering. In particular, multi-output Gaussian processes have been emerged as a promising tool for modeling these complex systems since they can exploit the inherent correlations and provide reliable uncertainty estimates. I…