List of Publications and Conference Talks
Publications
- Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak Water Resources Research 2022 [paper] [code]
- PDEBench: An Extensive Benchmark for Scientific Machine Learning Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Dan MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert NeurIPS 2022 Track on Datasets and Benchmarks [paper] [code] [data]
- Inferring Boundary Conditions in Finite Volume Neural Networks Coşku Can Horus, Matthias Karlbauer, Timothy Praditia, Martin V. Butz, Sergey Oladyshkin, Wolfgang Nowak, Sebastian Otte ICANN 2022 [paper] [code]
- Composing Partial Differential Equations with Physics-Aware Neural Networks Matthias Karlbauer, Timothy Praditia, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz ICML 2022 [paper] [poster] [code]
- Finite Volume Neural Network: Modeling Subsurface Contaminant Transport Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak ICLR 2021 Deep Learning for Simulation Workshop [paper] [poster] [code]
- Global sensitivity analysis of a CaO/Ca(OH)2 thermochemical energy storage model for parametric effect analysis Sinan Xiao, Timothy Praditia, Sergey Oladyshkin, Wolfgang Nowak Applied Energy 2021 [paper] [data]
- Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture Timothy Praditia, Thilo Walser, Sergey Oladyshkin, Wolfgang Nowak Energies 2020 [paper] [code] [data]
- Multiscale formulation for coupled flow-heat equations arising from single-phase flow in fractured geothermal reservoirs Timothy Praditia, Rainer Helmig, Hadi Hajibeygi Computational Geosciences 2018 [paper]
Talks
- Composing Partial Differential Equations with Physics-Aware Neural Networks Matthias Karlbauer, Timothy Praditia, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz ICML 2022 [paper] [poster] [code]
- Finite Volume Neural Networks: a Hybrid Modeling Strategy for Subsurface Contaminant Transport Timothy Praditia, Sergey Oladyshkin, Wolfgang Nowak AGU 2021 [abstract] [code]
- Finite Volume Neural Network: Modeling Subsurface Contaminant Transport Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak ICLR 2021 Deep Learning for Simulation Workshop [paper] [poster] [code]
- Universal Differential Equation for Diffusion-Sorption Problem in Porous Media Flow Timothy Praditia, Sergey Oladyshkin, Wolfgang Nowak EGU 2021 [abstract] [slides] [code]
- Prognosis of water levels in a moor groundwater system influenced by hydrology and water extraction using an artificial neural network Sascha Flaig, Timothy Praditia, Alexander Kissinger, Ulrich Lang, Sergey Oladyshkin, Wolfgang Nowak EGU 2021 [abstract] [slides] [code]
- Physics Informed Neural Network for porous media modelling Timothy Praditia, Sergey Oladyshkin, Wolfgang Nowak Interpore German Chapter Meeting 2021 [code]
- Using physics-based regularization in Artificial Neural Networks to predict thermochemical energy storage systems Timothy Praditia, Thilo Walser, Sergey Oladyshkin, Wolfgang Nowak AGU 2019 [abstract] [code]
- Multiscale finite volume method for sequentially coupled flow-heat system of equations in fractured porous media: application to geothermal systems Timothy Praditia, Rainer Helmig, Hadi Hajibeygi SIAM Conference on Mathematical and Computational Issues in the Geosciences 2017