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publications.html
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<a href="index.html" class="logo"><strong>Timothy Praditia</strong></a>
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<h1>List of Publications and Conference Talks</h1>
</header>
<hr class="major" />
<h2>Publications</h2>
<ul>
<li><b>Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network</b></br>
<i>Timothy Praditia</i>, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak</br>
Water Resources Research 2022</br>
[<a href="https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2022WR033149" target="_blank">paper</a>] [<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>PDEBench: An Extensive Benchmark for Scientific Machine Learning</b></br>
Makoto Takamoto, <i>Timothy Praditia</i>, Raphael Leiteritz, Dan MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert</br>
NeurIPS 2022 Track on Datasets and Benchmarks</br>
[<a href="https://openreview.net/pdf?id=dh_MkX0QfrK" target="_blank">paper</a>] [<a href="https://github.com/pdebench/PDEBench" target="_blank">code</a>] [<a href="https://darus.uni-stuttgart.de/dataverse/sciml_benchmark" target="_blank">data</a>]</li>
<li style="padding-top: 1em"><b>Inferring Boundary Conditions in Finite Volume Neural Networks</b></br>
Coşku Can Horus, Matthias Karlbauer, <i>Timothy Praditia</i>, Martin V. Butz, Sergey Oladyshkin, Wolfgang Nowak, Sebastian Otte</br>
ICANN 2022</br>
[<a href="papers/icann2022.pdf" target="_blank">paper</a>] [<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Composing Partial Differential Equations with Physics-Aware Neural Networks</b></br>
Matthias Karlbauer, <i>Timothy Praditia</i>, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz</br>
ICML 2022</br>
[<a href="https://proceedings.mlr.press/v162/karlbauer22a/karlbauer22a.pdf" target="_blank">paper</a>] [<a href="https://icml.cc/media/icml-2022/Slides/16236.pdf" target="_blank">poster</a>] [<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Finite Volume Neural Network: Modeling Subsurface Contaminant Transport</b></br>
<i>Timothy Praditia</i>, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak</br>
ICLR 2021 Deep Learning for Simulation Workshop</br>
[<a href="https://simdl.github.io/files/33.pdf" target="_blank">paper</a>] [<a href="https://simdl.github.io/posters/33-supp_Praditia%20et%20al%20-%20Poster.pdf" target="_blank">poster</a>] [<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Global sensitivity analysis of a CaO/Ca(OH)2 thermochemical energy storage model for parametric effect analysis</b></br>
Sinan Xiao, <i>Timothy Praditia</i>, Sergey Oladyshkin, Wolfgang Nowak</br>
Applied Energy 2021</br>
[<a href="https://www.sciencedirect.com/science/article/abs/pii/S0306261921000222" target="_blank">paper</a>] [<a href="https://darus.uni-stuttgart.de/dataverse/iws_pinn1" target="_blank">data</a>]</li>
<li style="padding-top: 1em"><b>Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture</b></br>
<i>Timothy Praditia</i>, Thilo Walser, Sergey Oladyshkin, Wolfgang Nowak</br>
Energies 2020</br>
[<a href="https://www.mdpi.com/1996-1073/13/15/3873" target="_blank">paper</a>] [<a href="https://github.com/timothypraditia/NARX_TCES" target="_blank">code</a>] [<a href="https://darus.uni-stuttgart.de/dataverse/iws_pinn1" target="_blank">data</a>]</li>
<li style="padding-top: 1em"><b>Multiscale formulation for coupled flow-heat equations arising from single-phase flow in fractured geothermal reservoirs</b></br>
<i>Timothy Praditia</i>, Rainer Helmig, Hadi Hajibeygi</br>
Computational Geosciences 2018</br>
[<a href="https://link.springer.com/content/pdf/10.1007/s10596-018-9754-4.pdf" target="_blank">paper</a>]</li>
</ul>
<hr class="major" />
<h2>Talks</h2>
<ul>
<li style="padding-top: 1em"><b>Composing Partial Differential Equations with Physics-Aware Neural Networks</b></br>
Matthias Karlbauer, <i>Timothy Praditia</i>, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz</br>
ICML 2022</br>
[<a href="https://proceedings.mlr.press/v162/karlbauer22a/karlbauer22a.pdf" target="_blank">paper</a>] [<a href="https://icml.cc/media/icml-2022/Slides/16236.pdf" target="_blank">poster</a>] [<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Finite Volume Neural Networks: a Hybrid Modeling Strategy for Subsurface Contaminant Transport</b></br>
<i>Timothy Praditia</i>, Sergey Oladyshkin, Wolfgang Nowak</br>
AGU 2021</br>
[<a href="https://ui.adsabs.harvard.edu/abs/2021AGUFM.H34F..02P/abstract" target="_blank">abstract</a>] [<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Finite Volume Neural Network: Modeling Subsurface Contaminant Transport</b></br>
<i>Timothy Praditia</i>, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak</br>
ICLR 2021 Deep Learning for Simulation Workshop</br>
[<a href="https://simdl.github.io/files/33.pdf" target="_blank">paper</a>] [<a href="https://simdl.github.io/posters/33-supp_Praditia%20et%20al%20-%20Poster.pdf" target="_blank">poster</a>] [<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Universal Differential Equation for Diffusion-Sorption Problem in Porous Media Flow</b></br>
<i>Timothy Praditia</i>, Sergey Oladyshkin, Wolfgang Nowak</br>
EGU 2021</br>
[<a href="https://ui.adsabs.harvard.edu/abs/2021EGUGA..23...49P/abstract" target="_blank">abstract</a>] [<a href="https://presentations.copernicus.org/EGU21/EGU21-49_presentation.pdf" target="_blank">slides</a>] [<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Prognosis of water levels in a moor groundwater system influenced by hydrology and water extraction using an artificial neural network</b></br>
Sascha Flaig, <i>Timothy Praditia</i>, Alexander Kissinger, Ulrich Lang, Sergey Oladyshkin, Wolfgang Nowak</br>
EGU 2021</br>
[<a href="https://ui.adsabs.harvard.edu/abs/2021EGUGA..23.3013F/abstract" target="_blank">abstract</a>] [<a href="https://presentations.copernicus.org/EGU21/EGU21-3013_presentation.pdf" target="_blank">slides</a>] [<a href="https://github.com/timothypraditia/lstm_swl" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Physics Informed Neural Network for porous media modelling</b></br>
<i>Timothy Praditia</i>, Sergey Oladyshkin, Wolfgang Nowak</br>
Interpore German Chapter Meeting 2021</br>
[<a href="https://github.com/CognitiveModeling/finn" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Using physics-based regularization in Artificial Neural Networks to predict thermochemical energy storage systems</b></br>
<i>Timothy Praditia</i>, Thilo Walser, Sergey Oladyshkin, Wolfgang Nowak</br>
AGU 2019</br>
[<a href="https://ui.adsabs.harvard.edu/abs/2019AGUFMIN32B..15P/abstract" target="_blank">abstract</a>] [<a href="https://github.com/timothypraditia/NARX_TCES" target="_blank">code</a>]</li>
<li style="padding-top: 1em"><b>Multiscale finite volume method for sequentially coupled flow-heat system of equations in fractured porous media: application to geothermal systems</b></br>
<i>Timothy Praditia</i>, Rainer Helmig, Hadi Hajibeygi</br>
SIAM Conference on Mathematical and Computational Issues in the Geosciences 2017</br>
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<h2>Get in touch</h2>
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