Microsoft Research's Probabilistic Bias Correction wins top honors in global extended weather forecasting competition
LesterMackey · x · 2026-10-15
Researchers at Microsoft Research, including Lester Mackey, Alexiji Lu, and Lorin Crawford, took top honors in a global forecasting competition with their Probabilistic Bias Correction method.
Why it matters:
- Weather forecasts become unreliable past two weeks, leaving a crucial gap for farmers and others
- The method improves extended-range probabilistic forecasting and shows promise for real-world use
Announced via the official Microsoft Research account as an AI for Science highlight.
More from Research
- Initialization matters far more than expected in LLM-driven scientific discovery, new study finds — BenBlaiszik · 2026-10-15
- RLVR is just RL — RLHF is the weird one, argues lateinteraction — lateinteraction · 2026-10-15
- Mathematician models OpenAI's 372-theorem drop as a self-organized criticality collapse — littmath · 2026-10-15
- RoPE long-context failures proven inevitable; training-free RoPE Profiler boosts accuracy up to 25% — zhaofeng_wu · 2026-10-15
- OpenAI's Quasi-Riemann proof sparks chain of results, Bhargava proves primitive root theorem — Singularitarian · 2026-10-15
- Applied Compute's Spork post-training recipe doubles chess puzzle solve-rate vs GRPO — ypatil125 · 2026-10-15