Liang F. (2005). Evidence Evaluation for Bayesian Neural Networks Using Contour Monte Carlo Neural Comput. 17

See more from authors: Liang F

References and models cited by this paper

Berg BA, Neuhaus T. (1991). Multicanonical algorithms for 1st order phase-transitions Physics Letters B. 267

Berger RL, Casella G. (2002). Statistical inference (2nd ed).

Bishop C. (1995). Neural Networks For Pattern Recognition.

Box GEP, Jenkins GM. (1970). Time series analysis: Forecasting and control.

Chatfield C. (2001). Time-series forecasting.

Cooper LN, Perrone MP. (1993). When networks disagree: Ensemble methods for hybrid neural networks Artificial neural networks for speech and vision.

Denison D, Holmes C, Mallick B, Smith AFM. (2002). Bayesian methods for nonlinear classification and regression.

Faraway J, Chatfield C. (1998). Time series forecasting with neural networks: A comparative study using the airline data J Royal Stat Soc Appl Stat. 47

Fisher RA. (1936). The use of multiple measurements in taxonomic problems Annual Of Eugenics. 7

Gelman A, Meng XL. (1998). Simulating normalizing constants: From importance sampling to bridge sampling to path sampling Statistical Science. 13

Geman S, Geman D. (1984). Stochastic relaxation, gibbs distributions, and the bayesian restoration of images. IEEE transactions on pattern analysis and machine intelligence. 6 [PubMed]

Green PJ. (1995). Reversible jump Markov chain Monte Carlo computation and Bayesian model determination Biometrika. 57

Grenander U, Miller M. (1994). Representations of knowledge in complex systems (with discussion) J Roy Statist Soc B. 56

Hastings WK. (1970). Monte Carlo sampling methods using Markov chains and their applications Biometrika. 57

Hurvich CM, Tsai CL. (1989). Regression and time series model selection in small samples Biometrika. 76

Ishikawa M. (2000). Structural learning and rule discovery Knowledge-based neurocomputing.

Kass RE, Raftery AE. (1995). Bayes factors J Amer Statist Assoc. 90

Kutner MH, Nachtsheim CJ, Neter J. (2004). Applied regression models (4th ed).

Liang F. (2003). Contour Monte Carlo: Theoretical results, practical considerations, and applications Tech Rep.

Liang F. (2004). Annealing contour Monte Carlo algorithm for structure optimization in an off-lattice protein model. The Journal of chemical physics. 120 [PubMed]

Liu JS. (2001). Monte Carlo strategies in scientific computing.

Mackay DJC. (1992). A practical Bayesian framework for back propagation networks Neural Comput. 4

Mackay DJC. (1992). The evidence framework applied to classification problems Neural Comput. 4

Mackay DJC. (1995). Bayesian non-linear modeling for the 1993 energy prediction competition Maximum entropy and Bayesian methods.

Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E. (1953). Equation of state calculations by fast computing machines J Chem Phys. 21

Müller P, Insua DR. (1998). Issues in Bayesian Analysis of Neural Network Models Neural computation. 10 [PubMed]

Neal RM. (1993). Probabilistic inference using Markov chain Monte Carlo methods Tech. Rep. No. CRG-TR-93-1.

Neal RM. (1996). Bayesian learning for neural networks.

Penny WD, Roberts SJ. (1999). Bayesian neural networks for classification: how useful is the evidence framework? Neural networks : the official journal of the International Neural Network Society. 12 [PubMed]

Ripley BD. (1994). Neural networks and related methods for classification J Roy Statist Soc B.

Smith AFM, Phillips DB. (1996). Bayesian model comparison via jump diffusions Markov chain Monte Carlo in practice.

Sugiura N. (1978). Further analysis of the data by Akaike's information criterion and the finite corrections Communications In Statistics-theory And Methods. 7

Thodberg HH. (1995). A review of Bayesian neural networks with an application to near infrared spectroscopy IEEE Trans Neural Networks. 7

Walker AM. (1969). On the asymptotic behavior of posterior distributions J Roy Statist Soc B. 31

Wang F, Landau DP. (2001). Efficient, multiple-range random walk algorithm to calculate the density of states. Physical review letters. 86 [PubMed]

References and models that cite this paper
This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.