I present a new Markov chain sampling method appropriate for distributions with isolated modes. Like the recently-developed method of \simulated tempering", the \tempered transition" method uses a series of distributions that interpolate between the distribution of interest and a distribution for which sampling is easier. The new method has the advantage that it does not require approximate val...

To investigate the effect of tempering treatment on mechanical properties and the microstructure of DIN 1.4021 Martensitic Stainless Steel, austenite treatment was conducted for the samples at 1000 ºC temperature for 60 min and then the samples were oil quenched. Later, tempering treatments were performed for the samples at 500 ºC and 700 ºC temperatures for 2 and 5 h, respectively; then quench...

Variational inference (VI) combined with data subsampling enables approximate posterior inference with large data sets for otherwise intractable models, but suffers from poor local optima. We first formulate a deterministic annealing approach for the generic class of conditionally conjugate exponential family models. This algorithm uses a temperature parameter that deterministically deforms the...

Local hardness increasing on the surface of the power plant rotor may result in severe damages. One major solution for rapid repairing of the rotors is the adaptive tempering heat treatment. For this purpose, after identification of the damaged rotor, initial investigations and tests (such as visual inspection, chemical analysis, nondestructive hardness measurements and replica or on-site metal...

mechanical properties of dissimilar weld joints between gost09ch16n4b (a martensitic stainless steel) and aisi 4130 thin sheets made by gas tungsten arc welding (gtaw) were studied using er410nimo and er100s-g filler metals in post weld heat treated conditions. heat treatment cycles consisted of austenitization at 900, 950 and 1000 °c for 1 h and this was followed by oil cooling and tempering a...

Simulated tempering (ST) is an established Markov chain Monte Carlo (MCMC) method for sampling from a multimodal density π(θ). Typically, ST involves introducing an auxiliary variable k taking values in a finite subset of [0, 1] and indexing a set of tempered distributions, say πk(θ) ∝ π(θ) k. In this case, small values of k encourage better mixing, but samples from π are only obtained when the...

This article introduces a new variant on the popular optimization method, simulated annealing, herein called modified discrete-state simulated annealing. A guide in practical implementation of simulated tempering is also provided. The algorithms are tested in the design of an ideal collector for a travelling wave tube amplifier. keywords: simulated annealing, simulated tempering, travelling wav...

The growing adoption of generalized-ensemble algorithms for biomolecular simulation has resulted in a resurgence in the use of the weighted histogram analysis method (WHAM) to make use of all data generated by these simulations. Unfortunately, the original presentation of WHAM by Kumar et al. is not directly applicable to data generated by these methods. WHAM was originally formulated to combin...

Tail estimates are developed for power law probability distributions with exponential tempering using a conditional maximum likelihood approach based on the upper order statistics. The method is demonstrated on simulated data from a tempered stable distribution, and for several data sets from geophysics and finance that show a power law probability tail with some tempering.

Restricted Boltzmann Machines (RBMs) are one of the fundamental building blocks of deep learning. Approximate maximum likelihood training of RBMs typically necessitates sampling from these models. In many training scenarios, computationally efficient Gibbs sampling procedures are crippled by poor mixing. In this work we propose a novel method of sampling from Boltzmann machines that demonstrate...