TEMPER: Temporal Encoder-Masked Probabilistic Ensemble Regressor for Time-Series Forecasting

arXiv:2609.23701 · stat.ML, cs.LG · Submitted 2026-09-20 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-09-20

Updated: 2026-09-20

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Calibration — 33× in this paper · explained in 7 episodes
• Ablation — 20× in this paper · explained in 1 episode
• Benchmark — 15× in this paper · explained in 2 episodes
• Probabilistic Forecasting — 7× in this paper · explained in 3 episodes
• Ablation study — 6× in this paper · explained in 1 episode
• Adam — 5× in this paper · explained in 2 episodes
• Regularization — 4× in this paper · explained in 3 episodes
• Time Series Forecasting — 4× in this paper · explained in 3 episodes
• Conformal Prediction — 2× in this paper · explained in 5 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Empirical Coverage — 1× in this paper · explained in 2 episodes
• Exchangeability — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
• Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
• N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
• N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting
• Categorical Reparameterization with Gumbel-Softmax
• The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
• Adam: A Method for Stochastic Optimization
• A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

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