TimeSeek pretrains one model for multi-task time series analytics
After large-scale pretraining, authors report state-of-the-art forecasting, anomaly detection, and classification in few-shot and zero-shot settings.
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Stories tagged #time-series
Paper measures sampling-frequency invariance of four time-series models
MOMENT, Chronos-2, Moirai-MoE and TimesFM are scored with new FSI, FDI and CDI metrics.
ConceptTime uses predictive surprise to interpret time-series classifiers
A frozen forecaster's prediction error both segments series and builds concepts, with no labels, language model, or expert vocabulary.
Current probabilistic time series foundation models show systematic miscalibration in uncertainty estimates
Probabilistic TSFMs exhibit distinct miscalibration patterns that standard metrics obscure, with post-hoc recalibration improving some but not all forms of calibration.
eCoMAE aligns evidential pretraining with observed time-series content
On IMPTC weather-shift tests, OOD accuracy rose from 0.7971 to 0.8068 and OOD AURC fell from 0.0718 to 0.0648.
TSFLab workbench for TSF research
TSFLab uses AI agents to improve time series forecasting research with lower costs and better accuracy.
FACTS-MAS weights forecasts by each evidence channel's skill
On housing inventory and unemployment claims for 15 U.S. metros, it beats TimesFM, while factor-adjusted exponential smoothing matches the fused forecast.
Random splits overstate machine-learning rainfall skill in Bangladesh
On 618,650 station-days, climatology already classified high-rainfall months at 88.4% accuracy, and learners added at most 0.8 points.
GAS-PFN adds road graphs to zero-shot traffic forecasts
At a 90-minute horizon it cuts MSE 34.0% versus TimePFN and 27.7% versus four general zero-shot forecasters.
Timestral models lead GIFT-Eval, TIME and fev-bench
Four probabilistic forecasters from 5M to 209M parameters ship with Hugging Face weights and GitHub inference code.
Pneuma releases aircraft time-series data for predictive maintenance
The public set has over 920 million steps, four aircraft types, and nine verified fault scenarios.
Timestral releases four open time-series models, topping GIFT-Eval
Authors say the 209M and 123M variants rank first and second on every metric of GIFT-Eval, TIME, and fev-bench.
CLOSURE detects time-series anomalies via consistency and recoverability
A diffusion reconstructor and a relation-closure operator are trained separately and calibrated only on normal data.
IBM Granite time-series models used for ensemble forecasting
No article body was available, so the post’s methods, results, and release status are unknown.
DISC combines time-series similarity metrics to predict transfer
After calibration, DISC scores pairs from metric values and tracks forecasting error better than any single metric.
NVIDIA introduces Kumo Forecast for time-series prediction
The post says it pairs pretrained time-series representations with historical pattern retrieval and interpretability.
TS2Vec-FM freezes a 1.6M-parameter time-series encoder
Kept frozen, it scores 83.3% on UCR-128 and 75.3% on UEA-27, within 0.3 points of MantisV2.
Mistral releases Timestral time-series foundation models
Mistral says its 209M model ranks first on GIFT-Eval, TIME and fev-bench while using about two-thirds the parameters of the prior leader.
Mistral releases Timestral, a 209M forecasting model family
The title says the family outperforms Google’s TimesFM-3; the article body was not in the provided text.
LagNet uses lag-structured operators for long-term forecasting
LagLayer ties history-to-future weights by relative lag and can replace temporal linear layers in existing models.
Data-Efficient Classifier Pretraining Through Diffusion Models
DiffPT uses diffusion pretraining to improve low-data classifiers, especially on medical images and time series.
PathFM: Fast Generative Forecasting of Multivariate Trajectories
PathFM generates full forecast trajectories with fast flow-matching sampling and leads a new path-score benchmark.
Twice Upon a Time: Complementary Representations for Time-Series Reasoning
A Qwen3-VL-8B dual-view time-series model lifts TSRBench accuracy from 44.5% to 53.2%.
PathFM: Fast Generative Forecasting of Multivariate Trajectories
PathFM uses flow matching to forecast full multivariate trajectories and beats baselines on a new path-score benchmark.