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cs.LG2026
Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch
Paul Brunzema, Louis Tiao, Nhat Le +3
Bayesian optimization (BO) has become the standard tool for sample-efficient optimization and owes its efficiency to uncertainty-aware search driven by generic statistical priors.…
cs.LG2025
Quantum-Boosted High-Fidelity Deep Learning
Feng-ao Wang, Shaobo Chen, Yao Xuan +12
A fundamental limitation of probabilistic deep learning is its predominant reliance on Gaussian priors. This simplistic assumption prevents models from accurately capturing the com…
cs.LG2019★ 1.1k cited
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
Shiyang Li, Xiaoyong Jin, Yao Xuan +4
Time series forecasting is an important problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation. In this…