Key papers

• LLM-as-a-Verifier: A General-Purpose Verification Framework (2026)
  Jacky Kwok et al.
  8.60
• A Statistical Framework for District Energy Long-term Electric Load Forecasting (2025)
  Emily Royal et al.
  8.41
• DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment (2025)
  Hao Wang et al.
  7.68
• Swift: An Autoregressive Consistency Model for Efficient Weather Forecasting (2025)
  Jason Stock et al.
  7.11
• Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices (2023)
  Bartosz Uniejewski
  6.39
• Seasonal Forecasting of Pan-Arctic Sea Ice with State Space Model (2025)
  Wei Wang et al.
  6.23
• Robust time series generation via Schr\"odinger Bridge: a comprehensive evaluation (2025)
  Alexandre Alouadi et al.
  6.12
• Mamba time series forecasting with uncertainty quantification (2025)
  Pedro Pessoa et al.
  6.12
• EnergyPatchTST: Multi-scale Time Series Transformers with Uncertainty Estimation for Energy Forecasting (2025)
  Wei Li et al.
  6.09
• Machine learning-based probabilistic forecasting of solar irradiance in Chile (2024)
  S\'andor Baran et al.
  5.73
• Probabilistic Forecasting for Building Energy Systems using Time-Series Foundation Models (2025)
  Young Jin Park et al.
  5.70
• Sensitivity Analysis of Priors in the Bayesian Dirichlet Auto-Regressive Moving Average Model (2025)
  Harrison Katz et al.
  5.70
• FreDF: Learning to Forecast in the Frequency Domain (2024)
  Hao Wang et al.
  5.23
• Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends! (2022)
  Luis Gruber and Gregor Kastner
  5.06
• Graph State-Space Models and Latent Relational Inference (2023)
  Daniele Zambon et al.
  4.52
• The Exact Worst-Case Tail Probability under Bounded Kurtosis (2026)
  Xiaoyu Li et al.
  4.33
• The Granularity Paradox: How Temporal Disaggregation Inflates In-Sample Fit and Compounds Out-of-Sample Error (2026)
  Hugo Moreira
  4.33
• From Graphs to Gradients: Physics-Inspired Structural Attribution for Cyber-Physical IoT Systems and Beyond (2026)
  Spyridon Evangelatos et al.
  4.33
• SafeImpute: Reliable Clinical Data Imputation via Conformal Selection (2026)
  Xinrui He et al.
  4.33
• Stochastic generator of trajectories from record data: application to the fluctuations of a glacier's frontal position from a sample of moraines (2026)
  Megret Maud (LSCE et al.
  4.33
• When do prophets profit in prediction markets? (2026)
  Anri Gu et al.
  4.33
• Boltzmann MapReduce: A Partition-Function Reduce for Forkable Sandboxes (2026)
  Yossi Eliaz
  4.33
• YUKTI: From Natural-Language Situations to Robust, Verifiable Decisions An Uncertainty-Typed Proposition IR, Assumption-Robust Pareto Frontiers, and a Regret Certificate (2026)
  Suyash Mishra
  4.33
• BatteryLake: Agentic, Physics-Grounded Curation of Heterogeneous Battery Aging Data and Benchmarking (2026)
  Tianwen Zhu et al.
  4.33
• Verification of Adaptive Agentic Controllers through Finite Rule Revision (2026)
  Roberto Garrone
  4.33
• Beyond Euclidean Clipping: Overcoming Exploration Collapse in LLM RL via Riemannian Isometric Policy Optimization (2026)
  Zhicheng Cai et al.
  4.33
• Filtering Harmful Actions Isn't Enough: Phantom Transfer in Agentic SDF (2026)
  Chinmayi Dixit
  4.33
• Incremental Transformer for Surrogate-Based Inverse Design of Geopolymer Mixtures (2026)
  Giansalvo Cirrincione et al.
  4.33
• From Checker to Forecaster: Code-Owned Evaluation of Model-Generated Strategic Routes Under Delayed Ground Truth (2026)
  Aleh Manchuliantsau
  4.33
• Calibrated e-CUSUM Decoding for Quantized Reasoning Models: Why Token Log-Probability Is the Wrong Observable for Decoding Monitors (2026)
  El Hassane Ettifouri (Novelis Research et al.
  4.33
• Compile, Then Page: Executable SOP Programs and a Capability-Gated Runtime for Procedural LLM Agents (2026)
  Chenglin Yu et al.
  4.33
• BattVAE-GP: Generative Modeling of Long-Horizon Battery Degradation with Uncertainty Quantification (2026)
  Raghvender Raghvender et al.
  4.33
• Removable Defects: The Economics and Limits of Deliberate Deficiency (2026)
  Cheng Qian
  4.33
• Statistical Properties and Power Analysis of Divergence Measures for Credit Risk Model Monitoring (2026)
  Abdullah Karasan et al.
  4.33
• Can Deep Generative Models Reproduce Non-Stationary Gaussian Random Fields? (2026)
  Daniel Kua et al.
  4.33
• FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance (2026)
  Jiaze Sun et al.
  4.27
• SPDM: Geometry-Modulated State Space Modeling with Manifold Constraints for Time Series Forecasting (2026)
  Xingsheng Chen et al.
  4.27
• Dirichlet-Guided Group Forecasting for Alleviating Over-smoothing in Time Series Forecasting (2026)
  Xingyu Zhang et al.
  4.27
• KFTD: Koopman-Fourier Time-Differentiable Network for Continuous Ocean Spatiotemporal Forecasting (2026)
  Qinghui Chen et al.
  4.27
• Relational and Sequential Conformal Inference for Energy Time Series over Graphs via Foundation Models (2026)
  Keivan Faghih Niresi et al.
  4.27
• Self-attention-based Diffusion Model for Time-series Imputation in Partial Blackout Scenarios (2025)
  Mohammad Rafid Ul Islam et al.
  4.25
• Real-time Bus Travel Time Prediction and Reliability Quantification: A Hybrid Markov Model (2025)
  Yuran Sun et al.
  4.25
• PaP-NF: Probabilistic Long-Term Time Series Forecasting via Prefix-as-Prompt Reprogramming and Normalizing Flows (2026)
  Minju Kim et al.
  4.22
• Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting (2026)
  Jinglin Li et al.
  4.22
• Anticipating Continued Global Fertility Decline via Neural Forecasting (2026)
  Daniel Ciganda et al.
  4.22
• Deep ZakaiJ: Structured Filtering for Jump-Diffusion Time Series Forecasting (2026)
  Yan Leng et al.
  4.22
• Modeling Dynamic Mixtures of Time-Delay Systems from Streaming Time Series (2026)
  Ren Fujiwara et al.
  4.22
• Nonlinear and Heavy-Tailed Predictability in Transition-Energy Financial Markets (2026)
  Kpante Emmanuel Gnandi (INSA Toulouse) et al.
  4.22
• Neural Stochastic Flows: Solver-Free Modelling and Inference for SDE Solutions (2025)
  Naoki Kiyohara et al.
  4.11
• Macroeconomic Forecasting and Machine Learning (2025)
  Ta-Chung Chi et al.
  3.97
• Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift (2025)
  Zhiyuan Zhao et al.
  3.97
• A More Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models (2025)
  Kin G. Olivares et al.
  3.92
• Probabilistic Forecasting Cryptocurrencies Volatility: From Point to Quantile Forecasts (2025)
  Grzegorz Dudek et al.
  3.86
• Evaluating LLMs on Real-World Forecasting Against Expert Forecasters (2025)
  Janna Lu
  3.81
• Forecasting Cryptocurrency Prices using Contextual ES-adRNN with Exogenous Variables (2025)
  Slawek Smyl and Grzegorz Dudek and Pawe{\l} Pe{\l}ka
  3.64
• Rethinking Remaining Useful Life Prediction with Scarce Time Series Data: Regression under Indirect Supervision (2025)
  Jiaxiang Cheng et al.
  3.64
• Online model learning with data-assimilated reservoir computers (2025)
  Andrea N\'ovoa et al.
  3.64
• SeqFusion: Sequential Fusion of Pre-Trained Models for Zero-Shot Time-Series Forecasting (2025)
  Ting-Ji Huang et al.
  3.59
• Towards Reliable Time Series Forecasting under Future Uncertainty: Ambiguity and Novelty Rejection Mechanisms (2025)
  Ninghui Feng et al.
  3.59
• Dual-Splitting Conformal Prediction for Multi-Step Time Series Forecasting (2025)
  Qingdi Yu et al.
  3.59