Researchers have developed MoFE, a new deep learning framework for forecasting cryptocurrency prices. The model combines Fourier Neural Operators with Mixture-of-Experts architecture to capture complex dynamics in cryptocurrency markets. It models volatility as a superposition of multiple frequency components and uses specialized experts to learn continuous function-to-function mappings. Experiments on Bitcoin datasets show that MoFE achieves state-of-the-art performance in both short-term and long-term forecasting horizons, reducing the phase-lag effect and delivering superior predictive gains. --- Why it matters: This matters because accurately predicting cryptocurrency prices is a challenging task that can have significant financial implications. Engineers and researchers working on AI for finance will be interested in MoFE's ability to improve forecasting performance and mitigate common issues like phase lag. Source: https://arxiv.org/abs/2608.17342