MaxEnt 2006 Workshop Final peer-reviewed papers

Tutorials

• A. Mohammad-Djafari, Maximum Entropy and Bayesian inference: Where do we stand and where do we go?
• B. Lecoutre, And if you were Bayesian without knowing it?
• A. Pohorille and E. Darve, A Bayesian approach to calculating free energies of chemical and biological systems.
• A. Caticha and A. Giffin, Updating probabilities.
• M. Costache, M. Lienou and M. Datcu, On Bayesian Inference, Maximum Entropy and Support Vector Machines Methods.

Information, Probability and Quantum systems

• L. F. Lemmens and Burhan Bakar, Probability assignment in a quantum statistical model.
• A. Vourdas, Phase space methods in continuous tensor products of Hilbert spaces.
• B.R. Gadgjiev, Jaynes' information theory formalism and critical phenomena in crystals with defects.

Source Separation

• C. Caiafa, E. Kuruoglu and A. Proto, A Minimax Entropy Method for Blind Separation of Dependent Components in Astrophysical Images.
• Y. Nishimori, S. Akaho and M. D. Plumbley, Riemannian Optimization Method on Generalized Flag Manifolds for Complex and Subspace ICA.
• R. Sameni, F. Vrins, F. Parmentier, C. Hérail, V. Vigneron, M. Verleysen, Ch. Jutten and M.B. Shamsollahi, Electrode Selection for Noninvasive Fetal Electrocardiogram Extraction using Mutual Information Criteria.
• Sh. Hosseini, R. Guidara, Y. Deville and Ch. Jutten, Maximum likelihood separation of spatially auto-correlated images using a Markov model.
• H. Hauksdottir, S. Moussaoui, F. Schmidt, Ch. Jutten, J. Chanussot and D. Brie, Mars Hyperspectral Data Processing using ICA and Bayesian Positive Source Separation.
• A. Ali Amini, M. Babaizadeh and Ch. Jutten, A fast method for sparse component analysis based on iterative detection-projection.
• B. Abbasi Bastami and H. Amindavar, Blind source separation using Maximum Entropy PDF estimation based on fractional moments.
• D. Aronsson, E. Bjonemo and M. Johansson, Estimation and detection of a periodic signal.

Information Geometry and Bayesian networks

• Simone Fiori, Extrinsic geometrical methods for neural blind deconvolution.
• C. Rodriguez, Anti-Data.
• A. Ramer, GraphMaxEnt
• R.C. Alamino and N. Caticha, Online Learning in Discrete Hidden Markov Models.
• Dawn E. Holmes, Toward a Generalized Bayesian Network.
• N. Caticha and J.P. Neirotti, The evolution of learning systems: to Bayes or not to be.
• F. Barbaresco, Information Intrinsic Geometric Flows.
• H. Snoussi and A. Mohammad-Djafari, Particle filtering on Riemannian Manifolds.
• J. Center, Learning complex classification models from large data sets.
• J.-F. Bercher, P. Jardin et B. Duriez, Bayesian classification and entropy for promoter prediction in human DNA sequences.
• C. Cafaro, S.A. Ali and A. Giffin, An Application of Reversible Entropic Dynamics on Curved Statistical Manifolds

Inverse problems

• K.M. Hanson, Probing the covariance matrix.
• D. Dodt, A. Dinklage, R. Fischer and D. Loffhagen, Analysis of Optical Emission Spectroscopy on Discharges.
• Udo v. Toussaint, Th. Schwarz-Selinger and Ch. Hopf, Bayesian Analysis of Ellipsometry Measurements.
• R. Preuss and A. Dinklage, Model Comparison in Plasma Energy Confinement Scaling revisited.
• V. Mazet, D. Brie and J. Idier, Decomposition of a chemical spectrum using a marked point process and a constant dimension model
• R. Fischer and V. Dose, Flexible and reliable profile estimation using exponential splines
• H. Dreier, A. Dinklage, R. Fischer, M. Hirsch and P. Kornejew Optimization of plasma diagnostics using Bayesian probability theory.
• K. Krajsek and R. Mester, Marginalized maximum a posteriori hyper-parameter estimation for global optical flow techniques.

Bayesian inference, Data and Image processing

• J. Skilling, Calibration and Interpolation.
• G. Delyon, Ph. Réfrégiér and F. Galland, Minimal stochastic complexity image partionning with non parametric statistical model.
• B. Ait-el-Fquih and F. Desbouvries, Bayesian smoothing algorithms in partially observed Markov chains.
• J. Lapuyade-Lahorgue and W. Pieczynski, Unsupervised Segmentation of Hidden Semi-Markov Non Stationary Chains.
• F. Desbouvries, Entropy computation in partially observed Markov chains.
• M. Soccorsi, M. Quartulli and M. Datcu, Space-Variant Model Fitting and Selection for Image Denoising and Information Extraction
• L. Gueguen, C. Le Men and M. Datcu, Analysis of Satellite Image Time Series Based on Information Bottleneck.
• H. Chaabouni and M. Datcu, Relevent Scatters Characterization in SAR Images.
• P. Brault and A. Mohammad-Djafari, Scalable region matching motion estimation based on an unsupervised spatial segmentation scheme
• A. Jalobeanu and J.A. Gutiérrez, Multisource data fusion for bandlimited signals: A Bayesian perspective.

Entropy: Basics and Computation

• V. Girardin and A. Sesboüé, Asymptotic study of an estimator of the entropy rate of a two-state Markov chain for one long trajectory.
• E. V. Vakarin and J.P. Badiali, Maximum entropy approach to characterization of random media.
• M. Grendar and G. Judge, Empirical Maximum Entropy Method.
• H. Gzyl, P.L.N. Inverardi and A. Tagliani, A New Bound for Discrete Distributions based on Maximum Entropy.
• M. Aminghafari and A. Mohammadpour, An alternative approach to the parametric empirical Bayes selection of wavelet thresholding.
• J.-F. Bercher, An amended MaxEnt formulation for deriving Tsallis factors, and associated issues.
• A. Solana-Ortega and V. Solana, Entropic Inference for Assigning Probabilities: Some Difficulties in Axiomatics and Applications.
• W. Borges and J.M. Stern, FBST: Compositionality.
• M. Pappalardo, MaxEnt Principle for Handing Uncertainly with Qualitative Values.

Nonparametric Bayesian Data Processing

• E. Barat and Th. Dautremer, Nonparametric Bayesian Estimation of X/$\gamma$-RAY Spectra using a hierarchical Polya Tree-Dirichlet Mixture Model.
• E. Barat, T. Dautremer and T. Trigano, Nonparametric Bayesian Estimation of Censored counters Intensity from the indicator data.

Entropy, Bayes and Applications

• M. Johansson, Competitive bidding in a certain class of auctions
• K. Kyo and H. Noda, Bayesian analysis of cross-prefectural production function with time varying structure in Japan.
• L. Dobrzynski, A. Holas, D. Satula and K. Szymanski, Interpretation of the M\"ossbauer Spectroscopy Data by the Maximum Entropy Method.
• L. Roemer and D. Cowling, Bayesian Methods in Ground Penetrating Radar.
• Tj. R. Bontekoe, Do Kester and J. Skilling, Scheduling for schools.
• P. M. Goggens and Y. Chi, , Electromagnetic Induction Landmine Detection using Bayesian Model Comparison.
• G. Verdoolaege, M.G. Von Hellermann, R. Jaspers, W. Biel, Integrated Bayesian estimation of $Z_eff$ in the TEXTOR Tokamak from Bremsstrahlung and CX inpurity density measurements
• E. KISS, A quasilinear parabolic type variational solution for Fourier's irreversible heat conduction process with minimum principles in case of finite signal rate.
• O. ESMER, Information theoric framework for the earthquake recurrence models: Methodica Firma Per Terra Non-Firma}