Trust-Region Variational Inference with Gaussian Mixture Models

Many methods for machine learning rely on approximate inference from intractable probability distributions. Variational inference approximates such distributions by tractable models that can be subsequently used for approximate inference. Learning sufficiently accurate approximations requires a rich model family and careful exploration of the relevant modes of the target distribution. We propose a method for learning accurate GMM approximations of intractable probability distributions based on insights from policy search by using information-geometric trust regions for principled exploration. For efficient improvement of the GMM approximation, we derive a lower bound on the corresponding optimization objective enabling us to update the components independently. Our use of the lower bound ensures convergence to a stationary point of the original objective. The number of components is adapted online by adding new components in promising regions and by deleting components with negligible weight. We demonstrate on several domains that we can learn approximations of complex, multimodal distributions with a quality that is unmet by previous variational inference methods, and that the GMM approximation can be used for drawing samples that are on par with samples created by state-of-theart MCMC samplers while requiring up to three orders of magnitude less computational resources

Additional Exploratory Photoelastic Studies in Stress Wave Propagation

In a previous report to the sponsor, the design and description of a high speed framing camera was presented along with several film strips representing the results of a series of qualitative investigations of dynamic stress wave phenomena. These studies included crack propagation, layered media, compressed bars and beams, and cross sections of rocket heads. As part of a continuing study in these and related fields, a final report is submitted covering (1) exploratory experimental studies of shock wave propagation initiated by explosive caps and by nitrogen shock wave impingement, and (2) theoretical studies of a series of dynamic stress wave problems carried out in conjunction with the overall problem

Screening fungi isolated from historic Discovery Hut on Ross Island, Antarctica for cellulose degradation

To survive in Antarctica, early explorers of Antarctica's Heroic Age erected wooden buildings and brought in large quantities of supplies. The introduction of wood and other organic materials may have provided new nutrient sources for fungi that were indigenous to Antarctica or were brought in with the materials. From 30 samples taken from Discovery Hut, 156 filamentous fungi were isolated on selective media. Of these, 108 were screened for hydrolytic activity on carboxymethyl cellulose, of which 29 demonstrated activities. Endo-1, 4-β-glucanase activity was confirmed in the extracellular supernatant from seven isolates when grown at 4°C, and also when they were grown at 15°C. Cladosporium oxysporum and Geomyces sp. were shown to grow on a variety of synthetic cellulose substrates and to use cellulose as a nutrient source at temperate and cold temperatures. The research findings from the present study demonstrate that Antarctic filamentous fungi isolated from a variety of substrates (wood, straw, and food stuffs) are capable of cellulose degradation and can grow well at low temperatures

The polymerization of acetylene on supported metal clusters

The polymerization of acetylene was studied by thermal programmed reaction on model catalysts consisting of size-selected Ag, Rh, and Pd atoms and Pdn (1 ≤ n ≤ 30) clusters on well-characterized MgO(111) thin films. In a single-pass heating cycle experiment, benzene, butadiene, and butane were catalyzed with different selectivities as function of cluster size: palladium and rhodium atoms selectively produce benzene, and the highest selectivity for butadiene is observed for Pd₆, whereas Pd₂₀ reveals the highest selectivity for butane. Ag atoms are inert. These results provide an atom-by-atom observation of the selectivity of small cluster catalysts

Spatially Localized Synthesis and Structural Characterization of Platinum Nanocrystals Obtained Using UV Light

Platinum nanocrystals with a fine control of the crystal domain size in the range 1.0–2.2 nm are produced by tuning the NaOH concentration during the UV-induced reduction of H$_2$PtCl$_6$ in surfactant-free alkaline ethylene glycol. The colloidal solutions obtained are characterized by transmission electron microscopy and pair distribution function analysis, allowing analysis of both atomic and nanoscale structures. The obtained nanoparticles exhibit a face-centered cubic crystal structure even for the smallest nanoparticles, and the cubic unit cell parameter is significantly reduced with decreasing crystallite size. It is further demonstrated how the “UV-approach” can be used to achieve spatial control of the nucleation and growth of the platinum nanocrystals, which is not possible by thermal reduction