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New optical system HAMON achieves 14% better forecasting accuracy

By PulseAugur Editorial · [2 sources] ·

Researchers have developed HAMON, a novel passive optical system for long-horizon time-series forecasting. This system encodes historical data onto an optical aperture and uses trainable phase masks with free-space diffraction to shape forecasts directly in the output field, eliminating the need for digital sequence-mixing layers during inference. HAMON has demonstrated superior performance on benchmarks like ETTm2 and ETTh2, outperforming strong digital baselines by up to 14% in MSE, while showing competitive results on weather data and mixed performance on traffic and electricity datasets. AI

IMPACT This passive optical approach could offer a new substrate for sequence mixing, potentially leading to more efficient forecasting models.

RANK_REASON The cluster contains a research paper detailing a new method for time-series forecasting.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Alper Y{\i}ld{\i}r{\i}m ·

    HAMON: Passive Optical Sequence Mixing for Long-Horizon Forecasting

    arXiv:2606.17028v1 Announce Type: cross Abstract: Simple linear and frequency-domain models remain surprisingly competitive in long-horizon time-series forecasting, and recent mechanistic evidence suggests that standard forecasting benchmarks may not require the dense superposed …

  2. arXiv cs.AI TIER_1 English(EN) · Alper Yıldırım ·

    HAMON: Passive Optical Sequence Mixing for Long-Horizon Forecasting

    Simple linear and frequency-domain models remain surprisingly competitive in long-horizon time-series forecasting, and recent mechanistic evidence suggests that standard forecasting benchmarks may not require the dense superposed representations that make transformers powerful in…

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