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RandONets: Shallow networks with random projections for learning linear and nonlinear operators

Journal of computational physics, 2025-01, Vol.520, p.113433, Article 113433

2025

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Implementation and (Inverse Modified) Error Analysis for Implicitly Templated ODE-Nets

SIAM journal on applied dynamical systems, 2024-12, Vol.23 (4), p.2643-2669

2024

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Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification

Journal of computational physics, 2024-12, Vol.519, p.113443, Article 113443

2024

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AI-Lorenz: A physics-data-driven framework for Black-Box and Gray-Box identification of chaotic systems with symbolic regression

Chaos, solitons and fractals, 2024-11, Vol.188 (C), p.115538, Article 115538

2024

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Data-driven discovery of chemotactic migration of bacteria via coordinate-invariant machine learning

BMC bioinformatics, 2024-10, Vol.25 (1), p.337

2024

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Nonlinear discrete-time observers with Physics-Informed Neural Networks

Chaos, solitons and fractals, 2024-09, Vol.186, p.115215, Article 115215

2024

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Machine learning for the identification of phase transitions in interacting agent-based systems: A Desai-Zwanzig example

Physical review. E, 2024-07, Vol.110 (1), Article 014121

2024

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Transformations establishing equivalence across neural networks: When have two networks learned the same task?

Chaos (Woodbury, N.Y.), 2024-07, Vol.34 (7)

2024

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Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era

Journal of computational physics, 2024-06, Vol.506, p.112910, Article 112910

2024

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Active learning of ternary alloy structures and energies

npj computational materials, 2024-05, Vol.10 (1), p.116-11, Article 116

2024

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Task-oriented machine learning surrogates for tipping points of agent-based models

Nature communications, 2024-05, Vol.15 (1), p.4117-4117, Article 4117

2024

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Staggered grids for multidimensional multiscale modelling

Computers & fluids, 2024-03, Vol.271, p.106167, Article 106167

2024

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A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms

SIAM journal on scientific computing, 2024-01, Vol.46 (2), p.A719-A743

2024

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Physics-agnostic and physics-infused machine learning for thin films flows: modelling, and predictions from small data

Journal of fluid mechanics, 2023-11, Vol.975, Article A41

2023

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Discrete-time nonlinear feedback linearization via physics-informed machine learning

Journal of computational physics, 2023-11, Vol.492, p.112408, Article 112408

2023

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Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space

Journal of computational physics, 2023-07, Vol.485, p.112072, Article 112072

2023

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Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data

Journal of mathematical biology, 2023-07, Vol.87 (1), p.15-15, Article 15

2023

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Gentlest Ascent Dynamics on Manifolds Defined by Adaptively Sampled Point-Clouds

The journal of physical chemistry. B, 2023-06, Vol.127 (23), p.5178-5189

2023

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Writing the Programs of Programmable Catalysis

ACS catalysis, 2023-06, Vol.13 (11), p.7457-7471

2023

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Machine learning-assisted crystal engineering of a zeolite

Nature communications, 2023-05, Vol.14 (1), p.3152-3152, Article 3152

2023

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Depolymerization of plastics by means of electrified spatiotemporal heating

Nature (London), 2023-04, Vol.616 (7957), p.488-494

2023

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Data-driven control of agent-based models: An Equation/Variable-free machine learning approach

Journal of computational physics, 2023-04, Vol.478, p.111953, Article 111953

2023

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Long-term p21 and p53 dynamics regulate the frequency of mitosis events and cell cycle arrest following radiation damage

Cell death and differentiation, 2023-03, Vol.30 (3), p.660-672

2023

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Staying the course: iteratively locating equilibria of dynamical systems on Riemannian manifolds defined by point-clouds

Journal of mathematical chemistry, 2023-03, Vol.61 (3), p.600-629

2023

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Black and gray box learning of amplitude equations: Application to phase field systems

Physical review. E, 2023-02, Vol.107 (2), Article 025305

2023

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RandONets: Shallow networks with random projections for learning linear and nonlinear operators

Implementation and (Inverse Modified) Error Analysis for Implicitly Templated ODE-Nets

Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification

AI-Lorenz: A physics-data-driven framework for Black-Box and Gray-Box identification of chaotic systems with symbolic regression

Data-driven discovery of chemotactic migration of bacteria via coordinate-invariant machine learning

Nonlinear discrete-time observers with Physics-Informed Neural Networks

Machine learning for the identification of phase transitions in interacting agent-based systems: A Desai-Zwanzig example

Transformations establishing equivalence across neural networks: When have two networks learned the same task?

Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era

Active learning of ternary alloy structures and energies

Task-oriented machine learning surrogates for tipping points of agent-based models

Staggered grids for multidimensional multiscale modelling

A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms

Physics-agnostic and physics-infused machine learning for thin films flows: modelling, and predictions from small data

Discrete-time nonlinear feedback linearization via physics-informed machine learning

Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space

Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data

Gentlest Ascent Dynamics on Manifolds Defined by Adaptively Sampled Point-Clouds

Writing the Programs of Programmable Catalysis

Machine learning-assisted crystal engineering of a zeolite

Depolymerization of plastics by means of electrified spatiotemporal heating

Data-driven control of agent-based models: An Equation/Variable-free machine learning approach

Long-term p21 and p53 dynamics regulate the frequency of mitosis events and cell cycle arrest following radiation damage

Staying the course: iteratively locating equilibria of dynamical systems on Riemannian manifolds defined by point-clouds

Black and gray box learning of amplitude equations: Application to phase field systems

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