Publications listed in chronological order.

• Eghtesad, A., Tan, J., Fuhg, J., Bouklas, N. (2024) “NN-EVP: A physics informed neural network-based elasto-viscoplastic framework for predictions of grain size-aware flow response,” International Journal of Plasticity, Volume 181, 104072
• Gregory, W., MacEachern, R., Takao, S., Lawrence, I., Nab, C., Deisenroth, M., Tsamados, M. (2024) “Scalable interpolation of satellite altimetry data with probabilistic machine learning,” Nature Communications, 15, 7453
• Van Wees, L. Shankar, K., Fuhg, J., Bouklas, N., Shade, P., Obstalecki, M. Kasemer, M. (2024) “Establishing the relationship between generalized crystallographic texture and macroscopic yield surfaces using partial input convex neural networks,” Materialia, Volume 36, 102151
• Graf, E., Townsend, A. (2024) “Numerical Instability of Algebraic Rootfinding Methods,” arxiv:2408.02805
• Au, C., Tsamados, M., Manescu, P., Takao, S. (2024) “ARISGAN: Extreme super-resolution of arctic surface imagery using generative adversarial networks,” Frontiers in Remote Sensing, Volume 5
• Bunker, J., Girolami, M., Lambley, H., Stuart, A., Sullivan, T.J. (2024) “Autoencoders in Function Space,” arxiv:2408.01362
• Bhattacharya, K., Kovachki, N., Rajan, A., Stuart, A., Trautner, M. (2024) “Learning Homogenization for Elliptic Operators,” SIAM Journal on Numerical Analysis, Volume 62, Issue 4
• Li, K., Ko, H., DiStasio, R., Damle, A. (2024) “Unambiguous and robust formulation for Wannier localization,” American Physical Society, Volume 110, Issue 8, 085127
• Chen, Y., Huang, D., Huang, J., Reich, S., Stuart, A. (2024) “Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows,” arxiv:2406.17263
• Lu, F., Zlobina, K., Rondoni, N., Teymoori, S Gomez, M. (2024) “Enhancing wound healing through deep reinforcement learning for optimal therapeutics,” Royal Society Open Science, Volume 11, Issue 7, 11240228
• Leung, S.C., Zhou, D., Bae, J. (2024) “Integrated Gradients for Optimal Surface Pressure Sensor Placement for Lift Prediction of an Airfoil Subject to Gust,” AIAA, 4148
• Sit, H., Keith, B., Bergen, K. (2024) “Improving Explainability of Softmax Classifiers Using a Prototype-Based Joint Embedding Method,” https://arxiv.org/abs/2407.02271
• Chen, W., Tsamados, M., Willatt, R., Takao, S., Brockley, D., de Rijke-Thomas, C., Francis, A., Johnson, T., Landy, J., Lawrence, I., Lee, S., Shirazi, D., Liu, W., Nelson, C., Stroeve, J., Hirata, L., Deisenroth, M. (2024) “Co-located OLCI optical imagery and SAR altimetry from Sentinel-3 for enhanced Arctic spring sea ice surface classification,” Frontiers in Remote Sensing, Volume 5
• Ding, Z., Ko, T., Yao, J., Lin, L., Li, X. (2024) “Random coordinate descent: A simple alternative for optimizing parameterized quantum circuits,” Physical Review Research, Volume 6, Issue 3,
• Padmanabha, G., Fuhg, J., Safta, C., Jones, R., Bouklas, N. (2024) “Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models,” arxiv:2407.00761
• Narayanan, A., Bergen, K. (2024) “Prototype-Based Methods in Explainable AI and Emerging Opportunities in the Geosciences,” https://openreview.net/pdf?id=iFjtwefAjZ
• Li, K., Damle, A. (2024) “Automating Variational Differentiation,” arxiv:2310.0945
• Calvello, E., Kovachki, N., Levine, M., Stuart, A. (2024) “Continuum Attention for Neural Operators,” arxiv:2406.06486
• Anderka, R., Deisenroth, M. Takao, S. (2024) “Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems,” arxiv:2402.17036
• Flynn, M., Wang, A., Alvarez, D.E., De Sa, C., Damle, A. (2024) “STAT: Shrinking Transformers After Training,” arXiv:2406.00061
• Akyildiz, O.D., Girolami, M., Stuart, A, Vadeboncoeur, A. (2024) “Efficient Prior Calibration From Indirect Data,” arXiv:2405.17955v1
• Wu, J., Levine, M.E., Schneider, T., Stuart, A. (2024) “Learning About Structural Errors in Models of Complex Dynamical Systems,” arXiv:2401.00035
• Yu, A., Mahoney, M.W., Erichson, B. (2024) “There is HOPE to Avoid HiPPOs for Long-memory State Space Models,” arXiv:2405.13975
• Boullé, N., Colbrook, M.J. (2024) “Multiplicative Dynamic Mode Decomposition,” arXiv:2405.05334
• Fuhg, J., Padmanabha, G., Bouklas, N., Bahmani, B., Sun, W., Vlassis, N., Flaschel, M., Carrara, P., De Lorenzis, L. (2024) “A review on data-driven constitutive laws for solids,” arxiv:2405.03658
• Damle, A., Glas, S., Townsend, A., Yu, A. (2024) “How to reveal the rank of a matrix?,” arXiv:2405.04330
• Lanthaler, S., Stuart, A. Trautner, M. (2024) “Discretization Error of Fourier Neural Operators,” https://arxiv.org/abs/2405.02221
• Key, O., Takao, S., Giles, D., Deisenroth, M. (2024) “Scalable Data Assimilation with Message Passing,” arxiv:2404.12968
• Persson, D., Boullé, N., Kressner, D. (2024) “Randomized Nyström approximation of non-negative self-adjoint operators,” arXiv:2404.00960
• Amsel, N., Chen, T., Keles, F.D., Halikias, D., Musco, C., Musco, C. (2024) “Fixed-sparsity matrix approximation from matrix-vector products,” arXiv:2402.09379
• Carrillo, J.A., Hoffman, F., Stuart, A.M., Vaes, U. (2024) “Statistical Accuracy of Approximate Filtering Methods,” arXiv:2402.01593
• Goldshlager, G.., Abrahamsen, N., Stuart, A, Lin, L. (2024) “A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions,” arXiv:2401.10190
• Colbrook, M.J., Li, Q., Raut, R.V. and Townsend, A., (2024) “Beyond expectations: residual dynamic mode decomposition and variance for stochastic dynamical systems,” Nonlinear Dynamics, 112(3), pp.2037-2061.
• Liu, T.J.B., Boullé, N., Sarfati, R., Earls, C.J. (2024) “LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law,” ICML Workshop on In-Context Learning.
• Boullé, N., Halikias, D., Otto, S.E., Townsend, A. (2024) “Operator learning without the adjoint,” arXiv:2401.17739
• Boullé, N., Colbrook, M.J. (2024) “On the Convergence of Hermitian Dynamic Mode Decomposition,” arXiv:2401.03192
• Boullé, N., Townsend, A. (2024) “A Mathematical Guide to Operator Learning,” Handbook of Numerical Analysis, 25, p. 83-125.
• Laakmann, F., Boullé, N. (2024) “Bifurcation analysis of a two-dimensional magnetic Rayleigh-Bénard problem,” Physica D: Nonlinear Phenomena, 467, 134270.
• Wang, C., Townsend, A. (2023) “Operator learning for hyperbolic partial differential equations,” arXiv:2312.17489
• Boullé, N., Herremans, A., Huybrechs, D. (2023) “Multivariate rational approximation of functions with curves of singularities,” arXiv:2312.13202
• Zvonek, J., Horning, A., Townsend, A. (2023) “ContHutch++: Stochastic trace estimation for implicit integral operators,” arxiv:2311.07035
• Armstrong, R., Buzali, A., and Damle, A. (2023) “Structure-Aware Analyses and Algorithms for Interpolative Decompositions,” https://arxiv.org/abs/2310.0945