2026
End-to-End Probabilistic Framework for Learning with Hard Constraints
ICLR 2026poster
We present ProbHardE2E, a probabilistic forecasting framework that incorporates hard operational/physical constraints and provides uncertainty quantification. Our methodology uses a novel differentiable probabilistic projection layer (DPPL) that can be combined with a wide range of neural network ar…