RAVEN proposes a regime-aware MoE architecture with cumulative importance thresholding and correlation-aware weighting to adaptively select temporal context for non-stationary financial forecasting.
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TS-Arena is a live pre-registration platform that evaluates time series forecasts on future data streams to eliminate information leakage.
Context-conditioned normalizing flows refine subnational survey distributions under severe data scarcity when conditioning covariates capture local heterogeneity.
citing papers explorer
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RAVEN: A Regime-Aware Variable-context Expert Network for Financial Time Series Forecasting
RAVEN proposes a regime-aware MoE architecture with cumulative importance thresholding and correlation-aware weighting to adaptively select temporal context for non-stationary financial forecasting.
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Context-Conditioned Generative Models Enable Subnational Refinement of Sparse Humanitarian Surveys
Context-conditioned normalizing flows refine subnational survey distributions under severe data scarcity when conditioning covariates capture local heterogeneity.