{"total":91,"rows":[{"id":"2202.11214","title":"FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators","created":"2022-02-22","cited_by_count":776,"area":null},{"id":"2301.10343","title":"ClimaX: A foundation model for weather and climate","created":"2023-01-24","cited_by_count":337,"area":null},{"id":"2212.12794","title":"GraphCast: Learning skillful medium-range global weather forecasting","created":"2022-12-24","cited_by_count":267,"area":null},{"id":"2306.12873","title":"FuXi: A cascade machine learning forecasting system for 15-day global weather forecast","created":"2023-06-22","cited_by_count":241,"area":null},{"id":"2311.07222","title":"Neural General Circulation Models for Weather and Climate","created":"2023-11-13","cited_by_count":239,"area":null},{"id":"2308.15560","title":"WeatherBench 2: A benchmark for the next generation of data-driven global weather models","created":"2023-08-29","cited_by_count":236,"area":null},{"id":"2306.03838","title":"Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere","created":"2023-06-06","cited_by_count":233,"area":null},{"id":"2209.15616","title":"Towards Multi-spatiotemporal-scale Generalized PDE Modeling","created":"2022-09-30","cited_by_count":197,"area":null},{"id":"2202.07575","title":"Forecasting Global Weather with Graph Neural Networks","created":"2022-02-15","cited_by_count":168,"area":null},{"id":"2310.10196","title":"Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook","created":"2023-10-16","cited_by_count":110,"area":null},{"id":"2312.03876","title":"Scaling transformer neural networks for skillful and reliable medium-range weather forecasting","created":"2023-12-06","cited_by_count":110,"area":null},{"id":"2209.04934","title":"Clifford Neural Layers for PDE Modeling","created":"2022-09-08","cited_by_count":92,"area":null},{"id":"2102.05107","title":"Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction models","created":"2021-02-09","cited_by_count":79,"area":null},{"id":"2203.16797","title":"When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning","created":"2022-03-31","cited_by_count":65,"area":null},{"id":"2306.10619","title":"Towards Stability of Autoregressive Neural Operators","created":"2023-06-18","cited_by_count":59,"area":null},{"id":"2310.02074","title":"ACE: A fast, skillful learned global atmospheric model for climate prediction","created":"2023-10-03","cited_by_count":56,"area":null},{"id":"2411.11268","title":"ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses","created":"2024-11-18","cited_by_count":54,"area":null},{"id":"2202.05656","title":"Evaluation of post-hoc interpretability methods in time-series classification","created":"2022-02-11","cited_by_count":53,"area":null},{"id":"2307.01909","title":"ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling","created":"2023-07-04","cited_by_count":47,"area":null},{"id":"2106.06898","title":"Learning Dissipative Dynamics in Chaotic Systems","created":"2021-06-13","cited_by_count":42,"area":null},{"id":"2101.09126","title":"Will Artificial Intelligence supersede Earth System and Climate Models?","created":"2021-01-22","cited_by_count":37,"area":null},{"id":"2104.10066","title":"EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task","created":"2021-04-16","cited_by_count":34,"area":null},{"id":"2104.00615","title":"Physics-informed neural networks for the shallow-water equations on the sphere","created":"2021-04-01","cited_by_count":32,"area":null},{"id":"2205.13158","title":"SwinVRNN: A Data-Driven Ensemble Forecasting Model via Learned Distribution Perturbation","created":"2022-05-26","cited_by_count":32,"area":null},{"id":"2201.10095","title":"RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation","created":"2022-01-25","cited_by_count":28,"area":null},{"id":"2311.06253","title":"Advancing Parsimonious Deep Learning Weather Prediction using the HEALPix Mesh","created":"2023-09-11","cited_by_count":28,"area":null},{"id":"2501.19374","title":"Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function","created":"2025-01-31","cited_by_count":28,"area":null},{"id":"2401.15305","title":"A Practical Probabilistic Benchmark for AI Weather Models","created":"2024-01-27","cited_by_count":25,"area":null},{"id":"2310.00813","title":"OceanNet: A principled neural operator-based digital twin for regional oceans","created":"2023-10-01","cited_by_count":24,"area":null},{"id":"2306.05420","title":"Scaling Spherical CNNs","created":"2023-06-08","cited_by_count":21,"area":null},{"id":"2309.10808","title":"AI Foundation Models for Weather and Climate: Applications, Design, and Implementation","created":"2023-09-19","cited_by_count":21,"area":null},{"id":"2206.03198","title":"Explaining the physics of transfer learning a data-driven subgrid-scale closure to a different turbulent flow","created":"2022-06-07","cited_by_count":20,"area":null},{"id":"2110.14423","title":"Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels","created":"2021-10-27","cited_by_count":19,"area":null},{"id":"2103.14430","title":"Combining distribution-based neural networks to predict weather forecast probabilities","created":"2021-03-26","cited_by_count":18,"area":null},{"id":"2205.00865","title":"WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models","created":"2022-05-02","cited_by_count":17,"area":null},{"id":"2103.09360","title":"Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformers","created":"2021-03-16","cited_by_count":15,"area":null},{"id":"2103.10935","title":"Data-driven geophysical forecasting: Simple, low-cost, and accurate baselines with kernel methods","created":"2021-02-13","cited_by_count":15,"area":null},{"id":"2104.12506","title":"Bridging observation, theory and numerical simulation of the ocean using Machine Learning","created":"2021-04-26","cited_by_count":15,"area":null},{"id":"2502.19750","title":"CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformer","created":"2025-02-27","cited_by_count":14,"area":null},{"id":"2103.06206","title":"Reservoir Computing as a Tool for Climate Predictability Studies","created":"2021-02-24","cited_by_count":13,"area":null},{"id":"2205.10972","title":"Global Extreme Heat Forecasting Using Neural Weather Models","created":"2022-05-23","cited_by_count":13,"area":null},{"id":"2206.14786","title":"ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts","created":"2022-06-29","cited_by_count":13,"area":null},{"id":"2206.04811","title":"Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems","created":"2022-06-09","cited_by_count":12,"area":null},{"id":"2402.06275","title":"Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics","created":"2024-02-09","cited_by_count":11,"area":null},{"id":"2502.07532","title":"Diffusion-LAM: Probabilistic Limited Area Weather Forecasting with Diffusion","created":"2025-02-11","cited_by_count":11,"area":null},{"id":"2309.09574","title":"Latent assimilation with implicit neural representations for unknown dynamics","created":"2023-09-18","cited_by_count":9,"area":null},{"id":"2403.10555","title":"KARINA: An Efficient Deep Learning Model for Global Weather Forecast","created":"2024-03-13","cited_by_count":9,"area":null},{"id":"2205.04601","title":"Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence","created":"2022-05-09","cited_by_count":8,"area":null},{"id":"2410.07472","title":"Exploring the design space of deep-learning-based weather forecasting systems","created":"2024-10-09","cited_by_count":8,"area":null},{"id":"2510.09734","title":"ARROW: An Adaptive Rollout and Routing Method for Global Weather Forecasting","created":"2025-10-10","cited_by_count":8,"area":null},{"id":"2112.04481","title":"What's Behind the Couch? Directed Ray Distance Functions (DRDF) for 3D Scene Reconstruction","created":"2021-12-08","cited_by_count":7,"area":null},{"id":"2301.01253","title":"Deep learning for bias-correcting CMIP6-class Earth system models","created":"2022-12-16","cited_by_count":6,"area":null},{"id":"2306.05812","title":"HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection","created":"2023-06-09","cited_by_count":6,"area":null},{"id":"2405.07395","title":"CaFA: Global Weather Forecasting with Factorized Attention on Sphere","created":"2024-05-12","cited_by_count":6,"area":null},{"id":"2106.12045","title":"Deep learning for improved global precipitation in numerical weather prediction systems","created":"2021-06-20","cited_by_count":5,"area":null},{"id":"2509.17601","title":"FastNet: Improving the physical consistency of machine-learning weather prediction models through loss function design","created":"2025-09-22","cited_by_count":5,"area":null},{"id":"2301.02959","title":"FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models","created":"2023-01-08","cited_by_count":4,"area":null},{"id":"2403.18864","title":"Interpretable Machine Learning for Weather and Climate Prediction: A Survey","created":"2024-03-24","cited_by_count":4,"area":null},{"id":"2411.07814","title":"Community Research Earth Digital Intelligence Twin (CREDIT)","created":"2024-11-09","cited_by_count":4,"area":null},{"id":"2210.12293","title":"DL-Corrector-Remapper: A grid-free bias-correction deep learning methodology for data-driven high-resolution global weather forecasting","created":"2022-10-21","cited_by_count":3,"area":null},{"id":"2304.04664","title":"Inductive biases in deep learning models for weather prediction","created":"2023-04-06","cited_by_count":3,"area":null},{"id":"2305.00100","title":"Temporal Subsampling Diminishes Small Spatial Scales in Recurrent Neural Network Emulators of Geophysical Turbulence","created":"2023-04-28","cited_by_count":3,"area":null},{"id":"2411.03223","title":"Beyond Grid Data: Exploring Graph Neural Networks for Earth Observation","created":"2024-11-05","cited_by_count":3,"area":null},{"id":"2412.10450","title":"Regional Weather Variable Predictions by Machine Learning with Near-Surface Observational and Atmospheric Numerical Data","created":"2024-12-11","cited_by_count":3,"area":null},{"id":"2505.14555","title":"Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting","created":"2025-05-20","cited_by_count":3,"area":null},{"id":"2206.11669","title":"Short-range forecasts of global precipitation using deep learning-augmented numerical weather prediction","created":"2022-06-23","cited_by_count":2,"area":null},{"id":"2308.04460","title":"The Compatibility between the Pangu Weather Forecasting Model and Meteorological Operational Data","created":"2023-08-07","cited_by_count":2,"area":null},{"id":"2402.13945","title":"Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning","created":"2024-02-21","cited_by_count":2,"area":null},{"id":"2405.06590","title":"Decomposing weather forecasting into advection and convection with neural networks","created":"2024-05-10","cited_by_count":2,"area":null},{"id":"2512.22814","title":"Long-Range Distillation: Distilling 10,000 Years of Simulated Climate into Long Timestep AI Weather Models","created":"2025-12-28","cited_by_count":2,"area":null},{"id":"2108.10855","title":"Quantum Artificial Intelligence for the Science of Climate Change","created":"2021-07-28","cited_by_count":1,"area":null},{"id":"2206.00893","title":"Leveraging Systematic Knowledge of 2D Transformations","created":"2022-06-02","cited_by_count":1,"area":null},{"id":"2211.00147","title":"A Machine Learning Tutorial for Operational Meteorology, Part II: Neural Networks and Deep Learning","created":"2022-10-31","cited_by_count":1,"area":null},{"id":"2309.14390","title":"Early Churn Prediction from Large Scale User-Product Interaction Time Series","created":"2023-09-25","cited_by_count":1,"area":null},{"id":"2407.19187","title":"Efficiently improving key weather variables forecasting by performing the guided iterative prediction in latent space","created":"2024-07-27","cited_by_count":1,"area":null},{"id":"2504.08766","title":"Towards scientific machine learning for granular material simulations -- challenges and opportunities","created":"2025-04-01","cited_by_count":1,"area":null},{"id":"2505.02506","title":"Exploring Design Choices for Autoregressive Deep Learning Climate Models","created":"2025-05-05","cited_by_count":1,"area":null},{"id":"2509.00653","title":"IndiaWeatherBench: A Dataset and Benchmark for Data-Driven Regional Weather Forecasting over India","created":"2025-08-31","cited_by_count":1,"area":null},{"id":"2605.18911","title":"Does Your Wildfire Prediction Model Actually Work, or Just Score Well?","created":"2026-05-14","cited_by_count":1,"area":null},{"id":"2606.18857","title":"Investigating Inductive Biases for Machine Learning Emulation of Sudden Stratospheric Warmings in Idealised Isca Simulations","created":"2026-06-17","cited_by_count":1,"area":null},{"id":"2402.14806","title":"Difference Learning for Air Quality Forecasting Transport Emulation","created":"2024-02-22","cited_by_count":0,"area":null},{"id":"2403.12366","title":"U-Net Kalman Filter (UNetKF): An Example of Machine Learning-assisted Ensemble Data Assimilation","created":"2024-03-19","cited_by_count":0,"area":null},{"id":"2404.01122","title":"Enhanced Precision in Rainfall Forecasting for Mumbai: Utilizing Physics Informed ConvLSTM2D Models for Finer Spatial and Temporal Resolution","created":"2024-04-01","cited_by_count":0,"area":null},{"id":"2407.01598","title":"Long-Term Prediction Accuracy Improvement of Data-Driven Medium-Range Global Weather Forecast","created":"2024-06-26","cited_by_count":0,"area":null},{"id":"2408.06262","title":"DUNE: A Machine Learning Deep UNet++ based Ensemble Approach to Monthly, Seasonal and Annual Climate Forecasting","created":"2024-08-12","cited_by_count":0,"area":null},{"id":"2506.14362","title":"HydroChronos: Forecasting Decades of Surface Water Change","created":"2025-06-17","cited_by_count":0,"area":null},{"id":"2510.10654","title":"Interactive Atmospheric Composition Emulation for Next-Generation Earth System Models","created":"2025-10-12","cited_by_count":0,"area":null},{"id":"2606.06348","title":"Performance Evaluation of GraphCast for Medium-Range Weather Forecasting over Brazil","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2607.03279","title":"From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model","created":"2026-07-03","cited_by_count":0,"area":null},{"id":"2609.33930","title":"Diffusion-Based Rollouts as a Stabilization Mechanism for Long-Horizon Environmental Forecasting","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2610.05296","title":"FlexCast: Adaptive Weather Forecasting from Arbitrary Field Sets","created":"2026-10-04","cited_by_count":0,"area":null}],"next_cursor":null}