Jaideep Pathak
Orcid: 0000-0002-3095-0256
According to our database1,
Jaideep Pathak
authored at least 18 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
2023
CoRR, 2023
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.
CoRR, 2023
FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators.
Proceedings of the Platform for Advanced Scientific Computing Conference, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
2022
DL-Corrector-Remapper: A grid-free bias-correction deep learning methodology for data-driven high-resolution global weather forecasting.
CoRR, 2022
Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence.
CoRR, 2022
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.
CoRR, 2022
2021
Proceedings of the Reservoir Computing, 2021
Using Data Assimilation to Train a Hybrid Forecast System that Combines Machine-Learning and Knowledge-Based Components.
CoRR, 2021
2020
Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics.
Neural Networks, 2020
Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations.
CoRR, 2020
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems.
CoRR, 2020
2019
Machine Learning Approaches for Data-Driven Analysis and Forecasting of High-Dimensional Chaotic Dynamical Systems.
PhD thesis, 2019
Using Machine Learning to Assess Short Term Causal Dependence and Infer Network Links.
CoRR, 2019
Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms.
CoRR, 2019
2018
Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model.
CoRR, 2018