B. Hunt

发表

Differentiable generalized synchronization of chaos

J. Yorke, E. Ott, B. Hunt, 1997 .

Onset of synchronization in large networks of coupled oscillators.

E. Ott, J. Restrepo, B. Hunt, 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

Reservoir observers: Model-free inference of unmeasured variables in chaotic systems.

R. Brockett, E. Ott, M. Girvan, 2017, Chaos.

Prevalence: a translation-invariant “almost every” on infinite-dimensional spaces

B. Hunt, 1992, math/9210220.

Four-dimensional ensemble Kalman filtering

J. Yorke, E. Ott, E. Kostelich, 2004 .

Approximating the largest eigenvalue of network adjacency matrices.

E. Ott, J. Restrepo, B. Hunt, 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

Synchronization in large directed networks of coupled phase oscillators.

Edward Ott, Juan G Restrepo, Brian R Hunt, 2005, Chaos.

Ensemble data assimilation for hyperbolic systems

Brian R. Hunt, Cecilia González-Tokman, B. Hunt, 2013 .

Structure in the parameter dependence of order and chaos for the quadratic map

Edward Ott, Brian R. Hunt, E. Ott, 1997 .

Predictability of Weather and Climate: Ensemble forecasting and data assimilation: two problems with the same solution?

Istvan Szunyogh, Edward Ott, Brian R. Hunt, 2006 .

A non‐Gaussian Ensemble Filter for Assimilating Infrequent Noisy Observations

Brian R. Hunt, John Harlim, B. Hunt, 2007 .

A comparative study of 4D-VAR and a 4D Ensemble Kalman Filter: perfect model simulations with Lorenz-96

B. Hunt, E. Fertig, J. Harlim, 2007 .

Evolving networks with multispecies nodes and spread in the number of initial links.

E. Ott, B. Hunt, Jong-Won Kim, 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

Duplication count distributions in DNA sequences.

Suzanne S. Sindi, J. Yorke, B. Hunt, 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

Balance and Ensemble Kalman Filter Localization Techniques

E. Kalnay, K. Ide, B. Hunt, 2011 .

Handling Nonlinearity in an Ensemble Kalman Filter: Experiments with the Three-Variable Lorenz Model

E. Kalnay, B. Hunt, Shu-Chih Yang, 2012 .

Synchronization in networks of networks: the onset of coherent collective behavior in systems of interacting populations of heterogeneous oscillators.

E. Ott, P. So, Ernest Barreto, 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

How projections affect the dimension spectrum of fractal measures

Brian R. Hunt, Vadim Kaloshin, B. Hunt, 1997 .

Emergence of synchronization in complex networks of interacting dynamical systems

Edward Ott, Juan G. Restrepo, Brian R. Hunt, 2006 .

Use of the breeding technique to estimate the structure of the analysis "errors of the day"

Istvan Szunyogh, Rebecca E. Morss, James A. Yorke, 2003 .

Handling nonlinearity in Ensemble Kalman Filter : Experiments with 1 the three-variable Lorenz model 2 3

E. Kalnay, B. Hunt, Shu-Chih Yang, 2011 .

The local ensemble transform Kalman filter and the running-in-place algorithm applied to a global ocean general circulation model

E. Kalnay, K. Ide, J. Carton, 2013 .

Correcting for Surface Pressure Background Bias in Ensemble-Based Analyses

E. Ott, B. Hunt, I. Szunyogh, 2009 .

A Guide to MATLAB: MATLAB Programming

Kevin R. Coombes, Brian R. Hunt, John E. Osborn, 2001 .

The Local Ensemble Transform Kalman Filter and its implementation on the NCEP global model at the University of Maryland

Elizabeth A. Satterfield, J. Yorke, E. Ott, 2007 .

Calculating topological entropy for transient chaos with an application to communicating with chaos

E. Ott, B. Hunt, J. Jacobs, 1998 .

Ensemble data assimilation with an adjusted forecast spread

B. Hunt, S. Rainwater, 2013 .

NOTES AND CORRESPONDENCE Extracting Envelopes of Rossby Wave Packets

E. Ott, B. Hunt, D. Patil, 2003 .

A Machine Learning‐Based Global Atmospheric Forecast Model

E. Ott, B. Hunt, Jaideep Pathak, 2020, Geophysical Research Letters.

A Hybrid Approach to Atmospheric Modeling That Combines Machine Learning With a Physics‐Based Numerical Model

B. Hunt, Jaideep Pathak, I. Szunyogh, 2021, Journal of Advances in Modeling Earth Systems.

THE LOCAL ENSEMBLE KALMAN FILTER OF THE UNIVERSITY OF MARYLAND

J. Yorke, E. Ott, E. Kostelich, 2004 .

Regularity of embeddings of infinite-dimensional fractal sets into finite-dimensional spaces

B. Hunt, V. Kaloshin, 1999 .

A local ensemble Kalman filter for atmospheric data assimilation

J. Yorke, E. Ott, E. Kostelich, 2002, physics/0203058.

A stretched exponential bound on the rate of growth of the number of periodic points for prevalent diffeomorphisms I

B. Hunt, V. Kaloshin, 2000, math/0012224.

Synchronization in large directed networks of coupled phase oscillators.

E. Ott, J. Restrepo, B. Hunt, 2005, Chaos.

Prevalence: a translation-invariant “almost every” on infinite-dimensional spaces

J. Yorke, T. Sauer, B. Hunt, 1992, math/9210220.

How projections affect the dimension spectrum of fractal

B. Hunt, B. Hunt, V. Kaloshin, 1997 .

Characterizing the dynamical importance of network nodes and links.

E. Ott, J. Restrepo, B. Hunt, 2006, Physical review letters.

Onset of synchronization in large networks of coupled oscillators.

E. Ott, J. Restrepo, B. Hunt, 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

Desynchronization waves and localized instabilities in oscillator arrays.

E. Ott, J. Restrepo, B. Hunt, 2004, Physical review letters.

Scale dependence of branching in arterial and bronchial trees.

E. Ott, J. Restrepo, B. Hunt, 2005, Physical review letters.

Emergence of coherence in complex networks of heterogeneous dynamical systems.

E. Ott, J. Restrepo, B. Hunt, 2006, Physical review letters.

Stabilizing Machine Learning Prediction of Dynamics: Noise and Noise-inspired Regularization

E. Ott, M. Girvan, B. Hunt, 2022, 2211.05262.

Comparison between Local Ensemble Transform Kalman Filter and PSAS in the NASA finite volume GCM

R. Todling, E. Kostelich, E. Kalnay, 2007, physics/0703066.

Stabilizing Machine Learning Prediction of Dynamics: Noise and Noise-inspired Regularization

E. Ott, M. Girvan, B. Hunt, 2022, ArXiv.

Optimal orbits of hyperbolic systems

B. Hunt, Guo-Cheng Yuan, 1999 .

Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics

Jaideep Pathak, Petros Koumoutsakos, Brian R. Hunt, 2019, Neural Networks.

Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model

Michelle Girvan, Jaideep Pathak, Edward Ott, 2018, Chaos.

Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach.

Jaideep Pathak, Zhixin Lu, Brian Hunt, 2018, Physical review letters.

Fractal properties of robust strange nonchaotic attractors in maps of two or more dimensions.

Edward Ott, Brian Hunt, Sang-Yoon Kim, 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

Fractal properties of robust strange nonchaotic attractors.

B R Hunt, E Ott, E. Ott, 2001, Physical review letters.

Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms pdf

Michelle Girvan, Petros Koumoutsakos, Jaideep Pathak, 2019, ArXiv.

Approximating invariant densities of metastable systems

Brian R. Hunt, Paul Wright, B. Hunt, 2009, Ergodic Theory and Dynamical Systems.

SLYRB measures: natural invariant measures for chaotic systems

Tien-Yien Li, B. Hunt, H. E. Nusse, 2002 .

Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter

Istvan Szunyogh, Eric J. Kostelich, Brian R. Hunt, 2005, physics/0511236.

Correlation dimension for iterated function systems

J. Yorke, B. Hunt, W. Chin, 1997 .

Reducing storage requirements for biological sequence comparison

Michael Roberts, James A. Yorke, Wayne Hayes, 2004, Bioinform..

A Preprocessor for Shotgun Assembly of Large Genomes

Michael Roberts, James A. Yorke, Brian R. Hunt, 2004, J. Comput. Biol..

Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data.

Jaideep Pathak, Edward Ott, Zhixin Lu, 2017, Chaos.

Extracting Envelopes of Nonzonally Propagating Rossby Wave Packets

Istvan Szunyogh, Edward Ott, Aleksey V. Zimin, 2006 .

Extracting Envelopes of Rossby Wave Packets

Istvan Szunyogh, Edward Ott, Aleksey V. Zimin, 2003 .

Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems

Jaideep Pathak, Istvan Szunyogh, Brian Hunt, 2020, Chaos.

The theory of chaotic attractors

Tien Yien Li, Brian R. Hunt, Judy Kennedy, 2004 .

Using Data Assimilation to Train a Hybrid Forecast System that Combines Machine-Learning and Knowledge-Based Components

E. Ott, M. Girvan, B. Hunt, 2021, Chaos.

Attractor reconstruction by machine learning.

Edward Ott, Zhixin Lu, Brian R Hunt, 2018, Chaos.

Local ensemble Kalman filtering in the presence of model bias

Istvan Szunyogh, Edward Ott, Brian R. Hunt, 2006 .

Coupled skinny baker's maps and the Kaplan–Yorke conjecture

B. Hunt, M. Gröger, 2013, 1303.0030.

Chapter 2 – Prevalence

Brian R. Hunt, Vadim Kaloshin, B. Hunt, 2010 .

A Guide to MATLAB®: For Beginners and Experienced Users

Brian R. Hunt, Ronald L. Lipsman, Jonathan Rosenberg, 2014 .

Long time algebraic relaxation in chaotic billiards.

E. Ott, B. Hunt, D. Armstead, 2002, Physical Review Letters.

Power-law decay and self-similar distributions in stadium-type billiards

E. Ott, B. Hunt, D. Armstead, 2004 .

Absolute Continuity of a Function and Uniform Integrability of Its Divided Differences

Brian R. Hunt, Patrick M. Fitzpatrick, B. Hunt, 2015, Am. Math. Mon..

Weight interpolation for efficient data assimilation with the Local Ensemble Transform Kalman Filter

Eugenia Kalnay, Neill E. Bowler, Brian R. Hunt, 2009 .

Four-dimensional local ensemble transform Kalman filter: numerical experiments with a global circulation model

B. Hunt, J. Harlim, 2007 .

Assessing a local ensemble Kalman filter: perfect model experiments with the National Centers for Environmental Prediction global model

Istvan Szunyogh, James A. Yorke, Eric J. Kostelich, 2005 .

Anomalous diffusion in infinite horizon billiards.

E. Ott, B. Hunt, D. Armstead, 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

Convex error growth patterns in a global weather model.

John Harlim, Eugenia Kalnay, Brian R Hunt, 2005, Physical review letters.

The Hausdorff dimension of graphs of Weierstrass functions

Brian R. Hunt, B. Hunt, 1998 .

Local Ensemble Transform Kalman Filter : An Efficient Scheme for Assimilating Atmospheric Data

Brian R. Hunt, John Harlim, B. Hunt, 2006 .

Stretched exponential estimates on growth of the number of periodic points for prevalent diffeomorphisms I

B. Hunt, V. Kaloshin, 2007 .

Newton interpolation polynomials, discretization method, and certain prevalent properties in dynamical systems

B. Hunt, A. Gorodetski, V. Kaloshin, 2006 .

A local ensemble transform Kalman filter data assimilation system for the NCEP global model

Istvan Szunyogh, James A. Yorke, Edward Ott, 2008 .

Assessing a local ensemble Kalman filter : perfect model experiments with the National Centers for Environmental Prediction global model

Istvan Szunyogh, James A. Yorke, Edward Ott, 2004 .

Mixed-Resolution Ensemble Data Assimilation

Brian R. Hunt, Sabrina Rainwater, B. Hunt, 2013 .

Atmospheric Dynamics for Efficient Ensemble Kalman Filtering

Istvan Szunyogh, James A. Yorke, Edward Ott, 2014 .

Four-dimensional local ensemble transform Kalman filter: numerical experiments with a global circulation model

B. Hunt, J. Harlim, BRIAN R. HUNT, 2007 .

Exploiting Local Low Dimensionality of the Atmospheric Dynamics for Efficient Ensemble Kalman Filtering

Istvan Szunyogh, James A. Yorke, Edward Ott, 2002 .

4 USE OF THE BREEDING TECHNIQUE IN THE ESTIMATION OF THE BACKGROUND COVARIANCE MATRIX FOR A QUASI-GEOSTROPHIC MODEL

D. J. Patil, E. Ott, J. A. Yorke, 2022 .

A non-Gaussian Ensemble Filter for Assimilating Infrequent Noisy Observations

B. Hunt, J. Harlim, 2007 .

When all solutions of x′ = −∑ qi(t) x(t − Ti(t)) oscillate

J. Yorke, B. Hunt, 1984 .

Prevalence: an addendum

J. Yorke, T. Sauer, B. Hunt, 1993 .

Comment on "Long time evolution of phase oscillator systems" [Chaos 19, 023117 (2009)].

Edward Ott, Thomas M Antonsen, Brian R Hunt, 2010, Chaos.

Nonlinear Processes in Geophysics Application of the Cross Wavelet Transform and Wavelet Coherence to Geophysical Time Series

Aslak Grinsted, John C. Moore, Svetlana Jevrejeva, 2022 .

Local low dimensionality of atmospheric dynamics.

B R Hunt, E Ott, J. Yorke, 2001, Physical review letters.

Use of the breeding technique to estimate the structure of the analysis "errors of the day"

J. Yorke, E. Kalnay, B. Hunt, 2003 .

Identifying Low-Dimensional Nonlinear Behavior in Atmospheric Data

Brian R. Hunt, James A. Carton, J. Carton, 2001 .

A Hybrid Atmospheric Model Incorporating Machine Learning Can Capture Dynamical Processes Not Captured by Its Physics‐Based Component

E. Ott, B. Hunt, I. Szunyogh, 2023, Geophysical Research Letters.

Observation bias correction with an ensemble Kalman filter

Hong Li, Istvan Szunyogh, Edward Ott, 2009 .

Dynamical origin for the occurrence of asynchronous hyperchaos and chaos via blowout bifurcations.

E. Ott, B. Hunt, Sang-Yoon Kim, 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

The prevalence of continuous nowhere differentiable functions

B. Hunt, 1994 .

When Cantor sets intersect thickly

J. Yorke, I. Kan, B. Hunt, 1993 .

The effect of projections on fractal sets and measures in Banach spaces

B. Hunt, W. Ott, V. Kaloshin, 2006, Ergodic Theory and Dynamical Systems.

Correlations in DNA sequences across the three domains of life

James A. Yorke, Brian R. Hunt, Sabyasachi Guharay, 2000 .

Fault-Detection Effectiveness and Fault Detectability in GUI Testing

D. O’Leary, B. Hunt, M. Zelkowitz, 2008 .

Estimating invariant measures and Lyapunov exponents

B. Hunt, 1996, Ergodic Theory and Dynamical Systems.

Separation of Chaotic Signals by Reservoir Computing

E. Ott, M. Girvan, B. Hunt, 2019, Chaos.

Bifurcation rigidity

Celso Grebogi, James A. Yorke, Hüseyin Koçak, 1999 .

From High Dimensional Chaos to Stable Periodic Orbits: The Structure of Parameter Space

Celso Grebogi, James A. Yorke, Brian R. Hunt, 1997 .

Newton interpolation polynomials, discretization method, and certain prevalent properties in dynamical systems

B. Hunt, A. Gorodetski, V. Kaloshin, 2006 .

A Guide to MATLAB®: For Beginners and Experienced Users

B. Hunt, R. Lipsman, Jonathan Rosenberg, 2014 .

A Hybrid Approach to Atmospheric Modeling That Combines Machine Learning With a Physics‐Based Numerical Model

B. Hunt, Jaideep Pathak, I. Szunyogh, 2022, Journal of Advances in Modeling Earth Systems.

Predictability of Weather and Climate: Ensemble forecasting and data assimilation: two problems with the same solution?

E. Ott, E. Kalnay, B. Hunt, 2006 .

Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics

Pantelis R. Vlachas, E. Ott, P. Koumoutsakos, 2019, Neural Networks.

Transitions to Bubbling of Chaotic Systems.

Ott, Hunt, Venkataramani, 1996, Physical review letters.