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Found 7 papers, 1 papers with code
FreDF: Learning to Forecast in Frequency Domain
Time series modeling is uniquely challenged by the presence of autocorrelation in both historical and label sequences.
Modeling Task Relationships in Multi-variate Soft Sensor with Balanced Mixture-of-Experts
Accurate estimation of multiple quality variables is critical for building industrial soft sensor models, which have long been confronted with data efficiency and negative transfer issues.
TMoE-P: Towards the Pareto Optimum for Multivariate Soft Sensors
We further present a Task-aware Mixture-of-Experts framework for achieving the Pareto optimum (TMoE-P) in multi-variate soft sensor, which consists of a stacked OMoE module and a POR module.
AttentionMixer: An Accurate and Interpretable Framework for Process Monitoring
An accurate and explainable automatic monitoring system is critical for the safety of high efficiency energy conversion plants that operate under extreme working condition.
Entire Space Counterfactual Learning: Tuning, Analytical Properties and Industrial Applications
As a basic research problem for building effective recommender systems, post-click conversion rate (CVR) estimation has long been plagued by sample selection bias and data sparsity issues.
An empirical evaluation of attention-based multi-head models for improved turbofan engine remaining useful life prediction
The results presented in this study demonstrate the importance of multi-head models and attention mechanisms to an improved understanding of the remaining useful life of industrial assets.
Analyze and Design Network Architectures by Recursion Formulas
The effectiveness of shortcut/skip-connection has been widely verified, which inspires massive explorations on neural architecture design.
