| Year | Rank | Type | Title / Venue / Authors |
|---|---|---|---|
| 2026 | J | jnl |
Reliab. Eng. Syst. Saf.
|
| 2026 | J | jnl |
J. Comput. Appl. Math.
|
| 2026 | J | jnl |
J. Comput. Phys.
|
| 2026 | J | jnl |
Adv. Eng. Informatics
|
| 2025 | J | jnl |
CoRR
|
| 2025 | J | jnl |
J. Sci. Comput.
|
| 2025 | J | jnl |
CoRR
|
| 2025 | J | jnl |
CoRR
|
| 2025 | J | jnl |
CoRR
|
| 2025 | J | jnl |
SIAM J. Sci. Comput.
|
| 2025 | J | jnl |
Eng. Appl. Artif. Intell.
|
| 2025 | J | jnl |
IEEE Geosci. Remote. Sens. Lett.
|
| 2025 | J | jnl |
J. Sci. Comput.
|
| 2024 | J | jnl |
Eng. Appl. Artif. Intell.
|
| 2024 | J | jnl |
CoRR
|
| 2024 | J | jnl |
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems.
Mach. Learn. Sci. Technol.
|
| 2024 | J | jnl |
CoRR
|
| 2024 | J | jnl |
Comput. Math. Appl.
|
| 2024 | J | jnl |
J. Comput. Phys.
|
| 2024 | J | jnl |
CoRR
|
| 2023 | J | jnl |
CoRR
|
| 2023 | J | jnl |
J. Comput. Phys.
|
| 2023 | J | jnl |
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems.
CoRR
|
| 2023 | J | jnl |
CoRR
|
| 2023 | J | jnl |
CoRR
|
| 2023 | J | jnl |
J. Comput. Appl. Math.
|
| 2022 | J | jnl |
SIAM J. Sci. Comput.
|
| 2022 | J | jnl |
CoRR
|
| 2022 | — | conf |
EMBC
|
| 2022 | J | jnl |
J. Comput. Phys.
|
| 2021 | J | jnl |
J. Sci. Comput.
|
| 2021 | J | jnl |
J. Comput. Appl. Math.
|
| 2019 | — | conf |
ISIE
|
| 2018 | J | jnl |
CoRR
|
| 2016 | J | jnl |
Appl. Math. Lett.
|
| 2014 | J | jnl |
J. Comput. Appl. Math.
|
| 2013 | J | jnl |
J. Appl. Math.
|
| 2012 | J | jnl |
J. Appl. Math.
|