TSCoNet: A Two-Stage Copula CNN-LSTM for Uncertainty-Aware Spatio-Temporal Forecasting

arXiv:2607.10410 · stat.ML, cs.LG · Submitted 2026-07-11 · Read on arXiv

Jongwook Kim, Jong-Min Kim

stat.ML, cs.LG

Submitted: 2026-07-11

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

Terminology

• Copula — 91× in this paper · explained in 2 episodes
• Accuracy — 44× in this paper · explained in 1 episode
• Calibration — 15× in this paper · explained in 9 episodes
• Non-stationarity — 11× in this paper · explained in 2 episodes
• Regularization — 8× in this paper · explained in 3 episodes
• Negative Log-Likelihood — 7× in this paper
• Trace — 7× in this paper · explained in 2 episodes
• Loss Function — 5× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 6 episodes
• Two-stage training — 4× in this paper · explained in 2 episodes
• Intrinsic Random Functions — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 3 episodes
• Clarity — 2× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 2× in this paper
• Inflation — 2× in this paper · explained in 2 episodes
• Two-Stage Training Strategy — 2× in this paper · explained in 5 episodes
• Uncertainty Quantification — 2× in this paper · explained in 9 episodes
• Absorb — 1× in this paper · explained in 1 episode
• Anisotropy — 1× in this paper · explained in 4 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 14 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 1× in this paper
• Interpretability — 1× in this paper · explained in 15 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Maximum Likelihood Estimation — 1× in this paper
• Memorization — 1× in this paper · explained in 4 episodes
• Neural Tangent Kernel (NTK) — 1× in this paper · explained in 2 episodes
• Papers — 1× in this paper · explained in 3 episodes
• Parameterization — 1× in this paper · explained in 2 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Reproducing Kernel Hilbert Space (RKHS) — 1× in this paper · explained in 7 episodes
• Spectral Bias — 1× in this paper · explained in 2 episodes
• Training Objective — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformers — 1× in this paper · explained in 2 episodes
• Two-Stage Mechanism — 1× in this paper · explained in 2 episodes

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