Corpus ID: 17545080

A Chaotic Dynamical System that Paints

  title={A Chaotic Dynamical System that Paints},
  author={T. Sahai and G. Mathew and A. Surana},
Can a dynamical system paint masterpieces such as Da Vinci's Mona Lisa or Monet's Water Lilies? Moreover, can this dynamical system be chaotic in the sense that although the trajectories are sensitive to initial conditions, the same painting is created every time? Setting aside the creative aspect of painting a picture, in this work, we develop a novel algorithm to reproduce paintings and photographs. Combining ideas from ergodic theory and control theory, we construct a chaotic dynamical… Expand
Autonomous Visual Rendering using Physical Motion
This paper addresses the problem of enabling a robot to represent and recreate visual information through physical motion, focusing on drawing using pens, brushes, or other tools. This work usesExpand
Discovery of a Phenomenological Dynamical Model for Predicting the El Niño-Southern Oscillation
The skill of the statistical as well as physics-based coupled climate models in predicting the El Ni\~no-Southern Oscillation (ENSO) is limited by their inability to represent the observed ENSOExpand


Handbook of Markov Chain Monte Carlo
A Markov chain Monte Carlo based analysis of a multilevel model for functional MRI data and its applications in environmental epidemiology, educational research, and fisheries science are studied. Expand
Proceedings of the Eighth Annual Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging
The symposium brings together individuals with technical experience developing computer based tools to solve aesthetic problems and people with artistic/design backgrounds who use and synthesize and these new tools. Expand
Variational algorithms for approximate Bayesian inference
A unified variational Bayesian (VB) framework which approximates computations in models with latent variables using a lower bound on the marginal likelihood and is compared to other methods including sampling, Cheeseman-Stutz, and asymptotic approximations such as BIC. Expand
Optimization with Sparsity-Inducing Penalties (Foundations and Trends(R) in Machine Learning)
Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. They were first dedicated to linear variable selection but numerous extensions have nowExpand
Journal of Chemical Physics
  • Nature
The first number of the new American Journal of Chemical Physics, which is published by the American Institute of Physics and has an editorial board comprising the leading American chemists andExpand
Machine learning
Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Expand
  • R. Rosenfeld
  • Medicine
  • Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
  • 2009
I am writing with a simple plea to balance the voluminous articles about treatment in your journal with a modicum of information about nature and caring effects to rekindle the perception of physicians as healers, not only treaters, who relish the gifts of nature, and foster the humanistic aspect of medicine that has thrived for millennia. Expand
The American statistician
Statistical Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1, 124, 254, 297 History Corner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Expand
Bayesian Inference
The Bayesian interpretation of probability is one of two broad categories of interpretations. Bayesian inference updates knowledge about unknowns, parameters, with information from data. TheExpand
Physics Letters B
  • Physics Letters B
  • 1987