What does it take to build next-gen #WeatherIntelligence? In #DTNsights, Renny Vandewege & Nic Wilson talk about #DTNWeatherHub, the customer problems it solves, & why #ProbabilisticForecasting matters when the forecast isn’t perfectly certain. Listen: dtn.link/53rk8w
#WeatherApp #WeatherResilience
What does it take to build next-gen #WeatherIntelligence? In #DTNsights, Renny Vandewege & Nic Wilson talk about #DTNWeatherHub, the customer problems it solves, & why #ProbabilisticForecasting matters when the forecast isn’t perfectly certain. Listen: dtn.link/53rk8w
#WeatherApp #WeatherResilience
Experiments show kinematic priors boost trajectory forecasting, with big gains in small or noisy datasets and modest gains in large-scale settings. #probabilisticforecasting
This section adds kinematic priors to trajectory forecasting, deriving Gaussian distributions from velocity, acceleration, speed‑heading, and steering. #probabilisticforecasting
This paper adds analytical kinematic priors for uncertainty across timesteps in trajectory forecasting, boosting performance and stability in traffic tasks. #probabilisticforecasting
It’s the go-to metric when forecasting with predictive distributions, not just point estimates.
#forecasting #datascience #uncertainty #probabilisticforecasting #crps #timeseries #analytics
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