Transfer Learning with Conformalized Quantile Regression for Solar PV Forecasting Under Load-Shedding-Driven Data Scarcity

arXiv:2609.26959 · cs.LG · Submitted 2026-09-22 · Read on arXiv

cs.LG

Submitted: 2026-09-22

Updated: 2026-09-22

Terminology

• Calibration — 25× in this paper · explained in 7 episodes
• Transfer Learning — 13× in this paper · explained in 10 episodes
• Empirical Coverage — 9× in this paper · explained in 2 episodes
• Conformal Prediction — 8× in this paper · explained in 5 episodes
• Exchangeability — 4× in this paper · explained in 2 episodes
• Conformal Quantile Regression — 3× in this paper
• Covariate Shift — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Uncertainty Quantification — 2× in this paper · explained in 8 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Bangladesh Power Development Board — 1× in this paper
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes

Sources

• Conformal Prediction for Stochastic Decision-Making of PV Power in Electricity Markets
• Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction
• Adam: A Method for Stochastic Optimization
• A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
• Computational Solar Energy -- Ensemble Learning Methods for Prediction of Solar Power Generation based on Meteorological Parameters in Eastern India

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks