Taniya Kapoor

Taniya Kapoor

Postdoc Researcher

Publications

Journal Papers

  1. Taniya Kapoor, Hongrui Wang, Anastasios Stamou*, Kareem El Sayed*, Alfredo Nunez, Daniel M Tartakovsky, Rolf Dollevoet. Neural differential equation-based two-stage approach for generalization of beam dynamics IEEE Transactions on Industrial Informatics(2024)
  2. Abhishek Chandra, Taniya Kapoor, Mitrofan Curti, Koen Tiels, Elena A. Lomonova. Characterizing nonlinear piezoelectric dynamics through deep neural operator learning Applied Physics Letters(2024)
  3. Taniya Kapoor, Hongrui Wang, Alfredo Nunez, Rolf Dollevoet. Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations Engineering Applications of Artificial Intelligence(2024)
  4. Taniya Kapoor, Hongrui Wang, Alfredo Nunez, Rolf Dollevoet(2023). Physics-informed neural networks for solving forward and inverse problems in complex beam systems IEEE Transactions on Neural Networks and Learning Systems(2023).

Conference Papers

  1. Taniya Kapoor*, Abhishek Chandra*, Daniel M Tartakovsky, Hongrui Wang, Alfredo Nunez, Rolf Dollevoet. Neural oscillators for generalization of physics-informed machine learning. Proceedings of the 38th AAAI Conference on Artificial Intelligence (2024).
  2. Taniya Kapoor, Hongrui Wang, Alfredo Núñez, Rolf Dollevoet. Physics-informed machine learning for moving load problems. Eurodyn XII International Conference on Structural Dynamics (2023).
  3. Taniya Kapoor, Hongrui Wang, Alfredo Núñez, Rolf Dollevoet. Predicting traction return current in electric railway systems through physics-informed neural networks. IEEE Symposium Series on Computational Intelligence (SSCI) (2022).

Workshop Papers

  1. Taniya Kapoor, Abhishek Chandra, Daniel Tartakovsky, Hongrui Wang, Alfredo Núñez, Rolf Dollevoet. Neural oscillators for generalizing parametric PDEs. NeurIPS 2023 Workshop: The Symbiosis of Deep Learning and Differential Equations III(2023)
  2. Somiya Kapoor, Abhishek Chandra, Taniya Kapoor, Mitrofan Curti. Gradient weighted physics-informed neural networks for capturing shocks in porous media flows. NeurIPS Workshop: Machine learning and the Physical Sciences(2023).

Preprints

  1. Chinmay Datar, Taniya Kapoor, Abhishek Chandra, Qing Sun, Iryna Burak, Erik Lien Bolager, Anna Veselovska, Massimo Fornasier, Felix Dietrich. Solving partial differential equations with sampled neural networks (2024)
  2. Abhishek Chandra*, Taniya Kapoor*, Bram Daniels, Mitrofan Curti, Koen Tiels, Daniel M Tartakovsky, Elena A Lomonova. Neural Oscillators for Magnetic Hysteresis Modeling(2023)

Posters

  1. Taniya Kapoor, Abhishek Chandra, Daniel Tartakovsky, Hongrui Wang, Alfredo Núñez, Rolf Dollevoet. Neural oscillators for generalizing parametric PDEs. NeurIPS 2023 Workshop: The Symbiosis of Deep Learning and Differential Equations III(2023)
  2. Somiya Kapoor, Abhishek Chandra, Taniya Kapoor, Mitrofan Curti. Gradient weighted physics-informed neural networks for capturing shocks in porous media flows. NeurIPS Workshop: Machine learning and the Physical Sciences(2023).
  3. Taniya Kapoor, Hongrui Wang, Alfredo Núñez, Rolf Dollevoet. PINNs for complex beam systems. CWI Autumn School, Amsterdam(2023)
  4. Abhishek Chandra*, Taniya Kapoor*, Bram Daniels, Mitrofan Curti, Koen Tiels, Daniel M Tartakovsky, Elena A Lomonova. Neural Oscillators for Magnetic Hysteresis Modeling. CWI Autumn School, Amsterdam(2023)
  5. Taniya Kapoor, Roberto Molinaro, Siddhartha Mishra. Physics Informed Neural Networks for Approximating Fully Nonlinear PDEs. London Mathematical Society Workshop on the Mathematics of Deep Learning(2022).