Merge pull request #99 from IamShubhamGupto/master

fix archive publications

content/publications/archive/_index.md

@@ -12,51 +12,49 @@ heroBackground: 'images/susan-q-yin-2JIvboGLeho-unsplash.jpg'
 
 * <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Guillaumin, A. P., & Zanna, L. **[Stochastic-Deep Learning Parameterization of Ocean Momentum Forcing](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021MS002534)** JAMES 2021
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Guillaumin A, Zanna L. **[Stochastic Deep Learning parameterization of Ocean Momentum Forcing.](https://doi.org/10.1029/2021MS002534)** _Journal of Advances in Modeling Earth Systems_ 2021.
+* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Zanna L, Bolton T. **[Deep Learning of Unresolved Turbulent Ocean Processes in Climate Models.](https://doi.org/10.1002/9781119646181.ch20)** In _Deep learning for the Earth Sciences_ 2021 (eds G. Camps-Valls, D. Tuia, X.X. Zhu and M. Reichstein). (author [link](https://zanna-research.github.io/files/Zanna-Bolton-2021.pdf))
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Zanna L, Bolton T. **[Deep Learning of Unresolved Turbulent Ocean Processes in Climate Models.](https://doi.org/10.1002/9781119646181.ch20)** In _Deep learning for the Earth Sciences_ 2021 (eds G. Camps-Valls, D. Tuia, X.X. Zhu and M. Reichstein). (author [link](https://laurezanna.github.io/files/Zanna-Bolton-2021.pdf))
+* Gentine P, Eyring V, Beucler T. **[Deep Learning for the Parametrization of Subgrid Processes in Climate Models](https://doi.org/10.1002/9781119646181.ch21)** In _Deep learning for the Earth Sciences_ 2021 (eds G. Camps-Valls, D. Tuia, X.X. Zhu and M. Reichstein).
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Gentine P, Eyring V, Beucler T. **[Deep Learning for the Parametrization of Subgrid Processes in Climate Models](https://doi.org/10.1002/9781119646181.ch21)** In _Deep learning for the Earth Sciences_ 2021 (eds G. Camps-Valls, D. Tuia, X.X. Zhu and M. Reichstein).
-
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Mooers G, Pritchard M, Beucler T, Ott J, Yacalis G, Baldi P, Gentine P. **[Assessing the Potential of Deep Learning for Emulating Cloud Superparameterization in Climate Models with Real-Geography Boundary Conditions.]( https://doi.org/10.1029/2020MS002385)**
+*  Mooers G, Pritchard M, Beucler T, Ott J, Yacalis G, Baldi P, Gentine P. **[Assessing the Potential of Deep Learning for Emulating Cloud Superparameterization in Climate Models with Real-Geography Boundary Conditions.]( https://doi.org/10.1029/2020MS002385)**
  _Journal of Advances in Modeling Earth Systems_ 2021
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Beucler T, Pritchard M, Rasp S, Ott J, Baldi P, Gentine P. **[Enforcing analytic constraints in neural networks emulating physical systems.](https://doi.org/10.1103/PhysRevLett.126.098302)** _Physical Review Letters_ 2021. (author [link](https://gentinelab.eee.columbia.edu/sites/default/files/content/PhysRevLett.126.098302.pdf))
+*  Beucler T, Pritchard M, Rasp S, Ott J, Baldi P, Gentine P. **[Enforcing analytic constraints in neural networks emulating physical systems.](https://doi.org/10.1103/PhysRevLett.126.098302)** _Physical Review Letters_ 2021. (author [link](https://gentinelab.eee.columbia.edu/sites/default/files/content/PhysRevLett.126.098302.pdf))
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Frezat H, Balarac G, Le Sommer J, Fablet R, Lguensat R. **[Physical invariance in neural networks for subgrid-scale scalar flux modeling.](https://doi.org/10.1103/PhysRevFluids.6.024607)** _Physical Review Fluids_ 2021. (author [link](https://hal.science/hal-03084215/file/2010.04663.pdf))
+*  Frezat H, Balarac G, Le Sommer J, Fablet R, Lguensat R. **[Physical invariance in neural networks for subgrid-scale scalar flux modeling.](https://doi.org/10.1103/PhysRevFluids.6.024607)** _Physical Review Fluids_ 2021. (author [link](https://hal.science/hal-03084215/file/2010.04663.pdf))
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> O’Gorman PA, Li Z, Boos WR, Yuval J. **[Response of extreme precipitation to uniform surface warming in quasi-global aquaplanet simulations at high resolution.](https://doi.org/10.1098/rsta.2019.0543)** _Philosophical Transactions of the Royal Society A_ 2021. (author [link](https://halo.mit.edu/src/ogorman_quasi_global_hires_precip_extremes_2021.pdf))
+*  O’Gorman PA, Li Z, Boos WR, Yuval J. **[Response of extreme precipitation to uniform surface warming in quasi-global aquaplanet simulations at high resolution.](https://doi.org/10.1098/rsta.2019.0543)** _Philosophical Transactions of the Royal Society A_ 2021. (author [link](https://pog.mit.edu/src/ogorman_quasi_global_hires_precip_extremes_2021.pdf))
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Yuval J, Hill CN, O'Gorman PA. **[Use of neural networks for stable, accurate and physically consistent parameterization of subgrid atmospheric processes with good performance at reduced precision.](https://doi.org/10.1029/2020GL091363)** _Geophysical Research Letter_ 2021.
+* Yuval J, Hill CN, O'Gorman PA. **[Use of neural networks for stable, accurate and physically consistent parameterization of subgrid atmospheric processes with good performance at reduced precision.](https://doi.org/10.1029/2020GL091363)** _Geophysical Research Letter_ 2021.
 
 ### 2020
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Yuval J, O’Gorman PA. **[Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions.](https://doi.org/10.1038/s41467-020-17142-3)** _Nature communications_ 2020.
+*  Yuval J, O’Gorman PA. **[Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions.](https://doi.org/10.1038/s41467-020-17142-3)** _Nature communications_ 2020.
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Zanna L, Bolton T. **[Data‐Driven Equation Discovery of Ocean Mesoscale Closures.](https://doi.org/10.1029/2020GL088376)** _Geophysical Research Letters_ 2020. (author [link](https://laurezanna.github.io/files/Zanna-Bolton-2020.pdf))
+* Zanna L, Bolton T. **[Data‐Driven Equation Discovery of Ocean Mesoscale Closures.](https://doi.org/10.1029/2020GL088376)** _Geophysical Research Letters_ 2020. (author [link](https://zanna-research.github.io/files/Zanna-Bolton-2020.pdf))
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Mohan S, Kadkhodaie Z, Simoncelli EP, Fernandez-Granda C. **[Robust and interpretable blind image denoising via bias-free convolutional neural networks](https://doi.org/10.48550/arXiv.1906.05478)** _ICLR_ 2020.
+* Mohan S, Kadkhodaie Z, Simoncelli EP, Fernandez-Granda C. **[Robust and interpretable blind image denoising via bias-free convolutional neural networks](https://doi.org/10.48550/arXiv.1906.05478)** _ICLR_ 2020.
 
 ### 2019
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Bolton T, Zanna L. **[Applications of Deep Learning to Ocean Data Inference and Subgrid Parameterization.](https://doi.org/10.1029/2018MS001472)** _J Adv Model Earth Syst_ 2019.
+* Bolton T, Zanna L. **[Applications of Deep Learning to Ocean Data Inference and Subgrid Parameterization.](https://doi.org/10.1029/2018MS001472)** _J Adv Model Earth Syst_ 2019.
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Held IM, Guo H, Adcroft A, Dunne JP, Horowitz LW, Krasting J, et al. **[Structure and Performance of GFDL’s CM4.0 Climate Model.](https://doi.org/10.1029/2019MS001829)** _J Adv Model Earth Syst_ 2019.
+* Held IM, Guo H, Adcroft A, Dunne JP, Horowitz LW, Krasting J, et al. **[Structure and Performance of GFDL’s CM4.0 Climate Model.](https://doi.org/10.1029/2019MS001829)** _J Adv Model Earth Syst_ 2019.
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Niall H. Robinson, Joe Hamman, Ryan Abernathey. **[Seven Principles for Effective Scientific Big-DataSystems.](https://doi.org/10.48550/arXiv.1908.03356)** _ArXiv190803356 Cs_ 2019.
+* Niall H. Robinson, Joe Hamman, Ryan Abernathey. **[Seven Principles for Effective Scientific Big-DataSystems.](https://doi.org/10.48550/arXiv.1908.03356)** _ArXiv190803356 Cs_ 2019.
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Izacard G, Mohan S, Fernandez-Granda C. **[Data-driven Estimation of Sinusoid Frequencies.](https://doi.org/10.48550/arXiv.1906.00823)** _Advances in Neural Information Processing Systems_ 2019.
+* Izacard G, Mohan S, Fernandez-Granda C. **[Data-driven Estimation of Sinusoid Frequencies.](https://doi.org/10.48550/arXiv.1906.00823)** _Advances in Neural Information Processing Systems_ 2019.
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Zhao WL, Gentine P, Reichstein M, Zhang Y, Zhou S, Wen Y, et al. **[Physics-constrained machine learning of evapotranspiration.](https://doi.org/10.1029/2019GL085291)** _Geophysical Research Letter_ 2019. (ResearchGate [link](https://www.researchgate.net/publication/337868554_Physics-Constrained_Machine_Learning_of_Evapotranspiration))
+* Zhao WL, Gentine P, Reichstein M, Zhang Y, Zhou S, Wen Y, et al. **[Physics-constrained machine learning of evapotranspiration.](https://doi.org/10.1029/2019GL085291)** _Geophysical Research Letter_ 2019. (ResearchGate [link](https://www.researchgate.net/publication/337868554_Physics-Constrained_Machine_Learning_of_Evapotranspiration))
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Yang T, Sun F, Gentine P, Liu W, Wang H, Yin J, et al. **[Evaluation and machine learning improvement of global hydrological model-based flood simulations.](https://doi.org/10.1088/1748-9326/ab4d5e)** _Environ Res Lett_ 2019.
+* Yang T, Sun F, Gentine P, Liu W, Wang H, Yin J, et al. **[Evaluation and machine learning improvement of global hydrological model-based flood simulations.](https://doi.org/10.1088/1748-9326/ab4d5e)** _Environ Res Lett_ 2019.
 
 ### 2018
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> O’Gorman PA, Dwyer JG. **[Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events.](https://doi.org/10.1029/2018MS001351)** _J Adv Model Earth Syst_ 2018.
+* O’Gorman PA, Dwyer JG. **[Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events.](https://doi.org/10.1029/2018MS001351)** _J Adv Model Earth Syst_ 2018.
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Gentine P, Pritchard M, Rasp S, Reinaudi G, Yacalis G. **[Could Machine Learning Break the Convection Parameterization Deadlock?](https://doi.org/10.1029/2018GL078202)** _Geophys Res Lett_ 2018.
+* Gentine P, Pritchard M, Rasp S, Reinaudi G, Yacalis G. **[Could Machine Learning Break the Convection Parameterization Deadlock?](https://doi.org/10.1029/2018GL078202)** _Geophys Res Lett_ 2018.
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Rasp S, Pritchard MS, Gentine P. **[Deep learning to represent subgrid processes in climate models.](https://doi.org/10.1073/pnas.1810286115)** _Proc Natl Acad Sci_ 2018.
+* Rasp S, Pritchard MS, Gentine P. **[Deep learning to represent subgrid processes in climate models.](https://doi.org/10.1073/pnas.1810286115)** _Proc Natl Acad Sci_ 2018.
 
-* <img src="/images/newlogo.png" style="width: 1.5vw; height: 1.5hw; vertical-align: middle;" alt="DOI icon"> Zanna L, Brankart JM, Huber M, Leroux S, Penduff T, Williams PD. **[Uncertainty and scale interactions in ocean ensembles: From seasonal forecasts to multidecadal climate predictions.](https://doi.org/10.1002/qj.3397)** _Q J R Meteorol Soc_ 2018.
+* Zanna L, Brankart JM, Huber M, Leroux S, Penduff T, Williams PD. **[Uncertainty and scale interactions in ocean ensembles: From seasonal forecasts to multidecadal climate predictions.](https://doi.org/10.1002/qj.3397)** _Q J R Meteorol Soc_ 2018.