Ioannis G. Kevrekidis
Authored:
(393f) Data-Driven Evolution Equation Reconstruction for Parameter-Dependent Nonlinear Dynamical Systems
2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)
(598a) Towards Global Optimization on Low-Dimensional Surrogates Via Manifold Learning
2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)
(257f) Explicit Model Predictive Control Using Nonlinear Intrinsic Variables
2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)
(658b) Manifold Learning for Measurements across Several Sensors: Alternating Diffusion, Data Fusion and Constructing Nonlinear Observers for Complex Chemical Reaction Networks
2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)
(126e) Recurrent Neural Networks, Numerical Integrators and Nonlinear System Identification
2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)
(675b) Modeling, Optimization, and Control of Bioprocesses Using Optogenetics
2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)
(344a) Coarse-Scale PDEs from Microscopic Observations Via Machine Learning
2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)
(324f) Grey-Box Identification for a Class of Nonlinear Dynamical Systems
2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)
(369i) Multiple Experts: Using the Mahalanobis Metric to Fuse Data from Different Partial Observations
2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)
(193c) When Have Two Networks Learned the Same Task? Data-Driven Transformations between System Representations
2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)
(753d) Data Driven Parameter Reduction
2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)
(110i) Learning Partial Differential Equations from Discrete Space Time Data: Convolutional and Recurrent Networks, and Their Relations to Traditional Numerical Methods
2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)
(373t) Exploring Energy Landscapes Using the Directed Graph Laplacian
2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)
(340e) Learning Coarse-Grained Partial Differential Equations from Fine-Scale Data Via Machine Learning
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(661f) On the Data-Driven Discovery and Calibration of Closures
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(299h) PDE+Pinn: Neural Identification and Solution of Partial Differential Equations on Partial Data
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(278g) Scientific Computation in the Latent Space through Manifold Learning
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(46a) Dynamical-Systems-Guided Learning of PDEs from Data
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(402g) Connections between Residual Networks and Explicit Numerical Integrators, with Applications to Identification of Noninvertible Dynamical Systems
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(278h) From Partial Data to out-of-Bounds Parameter and Observation Estimation with Diffusion Maps and Geometric Harmonics
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(340f) Assessing the Response of Dynamic Catalytic Surfaces
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(470f) Learning the Dynamics of Coupled Oscillator Systems through the Discovery of Emergent PDEs Via Artificial Neural Networks and Manifold Learning
2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)
(132c) Learning What to Learn: Some Data-Driven Twists in Linking System Identification, Manifold Learning, and (possibly) Causality Considerations
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(572f) Transport- and Reaction-Modeling of Nanocarriers for Cancer Therapeutics Via Experimental and in-Silico approaches
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(246f) Emergent Data-Driven Model Reductions for Coupled, Heterogeneous Agent-Based Systems
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(549e) Learning Coarse-Scale ODEs/PDEs from Microscopic Data: What and How Can We Learn It from Data?
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(476d) Computations and Optimization for Catalysts Under Dynamic Operation
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(226a) Learning Partial Differential Equations in Emergent Coordinates
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(303f) Initializing the Internal States of Lstm Neural Networks Via Manifold Learning
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(51f) From Brownian Dynamics Simulations and Experimental Observations of Colloidal Suspensions to Data-Driven Observables and Effective Sdes with Manifold Learning
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(203g) A Data-Driven Approach to Disentangled Parametrization of Relations, with an Application to Multisite Phosphorylation
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(346m) Learning Partial Differential Equations from Multiscale or Experimental Data: A Showcase on Bacterial Chemotaxis
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(560e) What Matters and What Does Not Matter: Parametrizing Common and Sensor-Specific Information across Multiple Sensors in Chemically Reacting Systems
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(284h) Emergent Evolution Equations from (multi-)Puzzle Tiles, with a Drosophila Embryonic Development Example
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(186d) Addressing Well-Posedness in a Data-Driven Manner: Model Problems and Physics-Informed Neural Networks
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(364l) Something Old, Something New: Generative Adversarial Approaches to Conditional Sampling in Complex System Simulations
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(303a) Data-Driven Development of Approximate Inertial Forms and Closures for Coarse-Scale Modeling of Multiphase Flows
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(246c) Pathologies of Neural Networks As Models of Discrete-Time Dynamical Systems
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(287d) Coarse-Grained Dynamics for Epidemics on Adaptive Networks
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(212b) Manifold Learning for Accelerating Coarse-Grained Optimization
2021 Annual Meeting (ISBN: 978-0-8169-1116-5)
(673f) Reaction-Diffusion Modeling of Nanocarrier Cocktails for Cancer Therapeutics
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(350b) Some of the Variables, Some of the Times, with Some Things Known: Identification with Partial Information
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(582a) Crystal Engineering of a Zeolite Using Machine Learning
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(298c) Quantifying the Invertibility of Neural Networks and Their Transformations
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(688g) Tipping Point Dynamics for Epidemiological Networks. Constructing Reduced Dynamical Data-Driven Models for Evolving Graphs
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(361n) Limits of Entrainment of Circadian Neuronal Networks
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(298d) Staying the Course: Locating Fixed Points of Dynamical Systems (and Critical Points of Potentials) on Riemannian Manifolds Defined By Sampling Point-Clouds
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(542c) A Data-Driven Approach to Determining Problem Well-Posedness
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(106c) Inverse Backward Analysis of Neural Approximants of Ordinary Differential Equations
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(624e) Accelerating Multiscale Global Optimization through Reduced Bayesian Optimization
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(542b) A Machine Learning Approach to Bridge the Gap between the Kuramoto-Sivashinsky and the Navier-Stokes Equations for Thin Film Flow
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(542d) Nonlinear Data Fusion from Heterogeneous Partial Observation Sets
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(542e) Learning What to Learn: Common and Sensor-Specific Information across Multiple Sensors, with Some Thoughts about Sensor Spoofing and Causality
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(182d) Modeling Tipping Points in the Reduced-Order Stochastic Dynamics of a Population of Interacting Agents
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
Associated proceedings:
2018 AIChE Annual Meeting
2019 AIChE Annual Meeting
2020 Virtual AIChE Annual Meeting
2021 Annual Meeting
2022 Annual Meeting