“I built this 3D sim to visualize how a 1D-CNN processes time-series data (the yellow box is the kernel sliding across time).”

“INSTRUCTIONS: 1. "title_en", "title_jp", "title_zh": Professional, engaging headlines.”

“In an industry in constant flux, sticking your neck out to predict what’s coming next may seem reckless.”

“Last January, I posted "3 predictions for what will happen in the LLM (Large Language Model) industry in 2025," and thanks to you, many people viewed it.”

“OpenForecaster 8B matches much larger proprietary models, with our training improving the accuracy, calibration, and consistency of predictions.”

“PRISM addresses the challenge through a learnable tree-based partitioning of the signal.”

“The resulting observable is mapped into a transparent decision functional and evaluated through realized cumulative returns and turnover.”

“Compared to existing state-of-the-art AI models, our system offers higher spatial resolution. It is cheap to train/run and requires no additional post-processing.”

“The paper introduces a general, model-agnostic training and inference framework for joint generative forecasting and shows how it enables assessment of forecast robustness and reliability using three complementary uncertainty quantification metrics.”

“We uncover distinct features on a wide range of length and time scales that correspond to tropical cyclones, atmospheric rivers, diurnal and seasonal behavior, large-scale precipitation patterns, specific geographical coding, and sea-ice extent, among others.”

“The SPDE-based extensions improve both point and probabilistic forecasts relative to standard benchmarks.”

“The multimodal Transformer achieves RMSE = 0.90 mm and R^2 = 0.97 on the test set on the eastern Ireland tile (E32N34).”

“The Transformer achieved the highest predictive accuracy with an R^2 of 0.9696.”

“A positive correlation between LAP and forecast accuracy indicates the presence and magnitude of lookahead bias.”

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“Incorporating scale gap metadata substantially improved the predictive performance of LLMs, with Gemini Stage 2 achieving the highest accuracy, with a mean absolute error of 5.43 cm, root mean square error of 8.58 cm, and R squared of 0.84 under optimal image conditions.”

“The paper finds that the value of priority access is discounted relative to risk-neutral valuation due to the difficulty of forecasting short-horizon volatility and bidders' risk aversion.”

“The GNN-TF model outperforms state-of-the-art methods, delivering superior predictive accuracy for predicting future tobacco usage.”

“The idea is to provide a lightweight way to: - upload a time series dataset, - train a set of baseline and widely used models (e.g. linear regression with lags, XGBoost, Prophet), - compare their forecasts and evaluation metrics on the same split.”

“I believe that every company benefiting from automation — which is most American companies — should... dedicate 1 percent of its profits to help retrain the people who are being displaced.”

“The skill of our distilled models scales with increasing synthetic training data, even when that data is orders of magnitude larger than ERA5. This represents the first demonstration that AI-generated synthetic training data can be used to scale long-range forecast skill.”

“DFINE significantly outperforms linear state-space models (LSSMs) in forecasting future neural activity.”

“Accounting for concepts such as locality and globality can be more relevant for achieving accurate results than adopting specific sequence modeling layers and that simple, well-designed forecasting architectures can often match the state of the art.”

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“submitted by /u/sci_guy0”

“Transformer models, which excel at handling long-term dependencies, have become significant architectural components for time series forecasting.”

“Deliberation significantly improves accuracy in scenario (2), reducing Log Loss by 0.020 or about 4 percent in relative terms (p = 0.017).”

“HINTS leverages the Friedkin-Johnsen (FJ) opinion dynamics model as a structural inductive bias to model evolving social influence, memory, and bias patterns.”

“The proposed LSTM-MLP model predicted the daily closing price of gold with the Mean absolute error (MAE) of $ 0.21 and the next month's price with $ 22.23.”

“The experimental results indicate that the proposed model achieves mean absolute percentage errors (MAPE) of 3.243% and 2.641% for window lengths 20 and 15, respectively.”

“TimePerceiver is a unified encoder-decoder forecasting framework that is tightly aligned with an effective training strategy.”

“CRC consistently improves accuracy, while an in-depth ablation study confirms that its core safety mechanisms ensure exceptionally high non-degradation rates (NDR), making CRC a correction framework suited for safe and reliable deployment.”

“The paper develops a tractable inferential framework that avoids label enumeration and direct simulation of the latent state, exploiting a duality between the diffusion and a pure-death process on partitions.”

“At a 70-day forecast horizon, the proposed TimeXer-Exog model achieves a mean squared error (MSE) 1.08e8, outperforming the univariate TimeXer baseline by over 89 percent.”

“The proposed methods yield improved coverage properties and computational efficiency relative to existing approaches.”

“Experiments on Swedish and MRMS datasets show consistent improvements over state-of-the-art methods, achieving over 60 % and 19% gains in heavy-rainfall CSI at an 80-minute lead time.”

“Incorporating cosmic-ray information further improves 48-hour forecast skill by up to 25.84% (from 0.178 to 0.224).”

“ANWM significantly outperforms existing world models in long-distance visual forecasting and improves UAV navigation success rates in large-scale environments.”

“MASFIN delivered a 7.33% cumulative return, outperforming the S&P 500, NASDAQ-100, and Dow Jones benchmarks in six of eight weeks, albeit with higher volatility.”

“The study demonstrates that with PDx we can mitigates value erosion for digital lenders, particularly in short-term, small-ticket loans, where borrower behavior shifts rapidly.”

“Compact Ca II K brightenings precede solar flares.”

“QFWP achieves lower RMSE and higher directional accuracy at all batch sizes, while QLSTM reaches the highest throughput at batch size 64, revealing a clear speed accuracy Pareto frontier.”

“The research focuses on energy-efficient liquid cooling in AI data centers.”

“The improved forecast enables more accurate reserve estimation, reducing procurement costs by 5.53% in 2035 scenario compared to a well-validated numerical weather prediction model. Applying the risk-based aggregation further reduces total production costs by 7.21%.”

“RIPCN introduces a dynamic impedance evolution network that captures directional traffic transfer patterns driven by road congestion level and flow variability, revealing the direct causes of uncertainty and enhancing both reliability and interpretability.”

“RefineBridge improves financial forecasting by leveraging foundation models.”

“"Our findings indicate that the UDE model is much more data efficient, needing only 20% of data for a correct forecast, whereas the Neural ODE requires 90%."”

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“The study focuses on high-dimensional multi-task forecasting within a cloud-native backend.”

“Our SER-based model provides superior performance compared with other existing text-driven models to forecast stock returns out of sample and offers highly interpretable feature structures to examine the mechanisms underlying the stock return predictability.”