Fully distributed Bayesian optimization with stochastic policies

Bayesian optimization has become a popular method for high-throughput computing, like the design of computer experiments or hyperparameter tuning of expensive models, where sample efficiency is mandatory. In these applications, distributed and scalable architectures are a necessity. However, Bayesian optimization is mostly sequential. Even parallel variants require certain computations between samples, limiting the parallelization bandwidth. Thompson sampling has been previously applied for distributed Bayesian optimization. But, when compared with other acquisition functions in the sequential setting, Thompson sampling is known to perform suboptimally. In this paper, we present a new method for fully distributed Bayesian optimization, which can be combined with any acquisition function. Our approach considers Bayesian optimization as a partially observable Markov decision process. In this context, stochastic policies, such as the Boltzmann policy, have some interesting properties which can also be studied for Bayesian optimization. Furthermore, the Boltzmann policy trivially allows a distributed Bayesian optimization implementation with high level of parallelism and scalability. We present results in several benchmarks and applications that show the performance of our method

Occupancy Anticipation for Efficient Exploration and Navigation

State-of-the-art navigation methods leverage a spatial memory to generalize to new environments, but their occupancy maps are limited to capturing the geometric structures directly observed by the agent. We propose occupancy anticipation, where the agent uses its egocentric RGB-D observations to infer the occupancy state beyond the visible regions. In doing so, the agent builds its spatial awareness more rapidly, which facilitates efficient exploration and navigation in 3D environments. By exploiting context in both the egocentric views and top-down maps our model successfully anticipates a broader map of the environment, with performance significantly better than strong baselines. Furthermore, when deployed for the sequential decision-making tasks of exploration and navigation, our model outperforms state-of-the-art methods on the Gibson and Matterport3D datasets. Our approach is the winning entry in the 2020 Habitat PointNav Challenge. Project page: http://vision.cs.utexas.edu/projects/occupancy_anticipation/Comment: Accepted in ECCV 2020. 19 pages, 6 figures, appendix at en

Joint Optical Flow and Temporally Consistent Semantic Segmentation

The importance and demands of visual scene understanding have been steadily increasing along with the active development of autonomous systems. Consequently, there has been a large amount of research dedicated to semantic segmentation and dense motion estimation. In this paper, we propose a method for jointly estimating optical flow and temporally consistent semantic segmentation, which closely connects these two problem domains and leverages each other. Semantic segmentation provides information on plausible physical motion to its associated pixels, and accurate pixel-level temporal correspondences enhance the accuracy of semantic segmentation in the temporal domain. We demonstrate the benefits of our approach on the KITTI benchmark, where we observe performance gains for flow and segmentation. We achieve state-of-the-art optical flow results, and outperform all published algorithms by a large margin on challenging, but crucial dynamic objects.Comment: 14 pages, Accepted for CVRSUAD workshop at ECCV 201

Parameter estimation for biochemical reaction networks using Wasserstein distances

We present a method for estimating parameters in stochastic models of biochemical reaction networks by fitting steady-state distributions using Wasserstein distances. We simulate a reaction network at different parameter settings and train a Gaussian process to learn the Wasserstein distance between observations and the simulator output for all parameters. We then use Bayesian optimization to find parameters minimizing this distance based on the trained Gaussian process. The effectiveness of our method is demonstrated on the three-stage model of gene expression and a genetic feedback loop for which moment-based methods are known to perform poorly. Our method is applicable to any simulator model of stochastic reaction networks, including Brownian Dynamics.Comment: 22 pages, 8 figures. Slight modifications/additions to the text; added new section (Section 4.4) and Appendi

Near-to mid-IR spectral purity transfer with a tunable frequency comb: methanol frequency metrology over a record frequency span

We report the development and operation of a frequency-comb-assisted high-resolution mid-infrared molecular spectrometer combining high spectral purity, SI-traceability, wide tunability and high sensitivity. An optical frequency comb is used to transfer the spectral purity of a SI-traceable 1.54 $\mu$m metrology-grade frequency reference to a 10.3 $\mu$m quantum cascade laser (QCL). The near-infrared reference is operated at the French time/frequency metrology institute, calibrated there to primary frequency standards, and transferred to Laboratoire de Physique des Lasers via the REFIMEVE fiber network. The QCL exhibits a sub-10 --15 frequency stability from 0.1 to 10 s and its frequency is traceable to the SI with a total uncertainty better than 4 x 10 --14 after 1-s averaging time. We have developed the instrumentation allowing comb modes to be continuously tuned over 9 GHz resulting in a QCL of record spectral purity uninterruptedly tunable at the precision of the reference over an unprecedented span of 1.4 GHz. We have used our apparatus to conduct sub-Doppler spectroscopy of methanol in a multi-pass cell, demonstrating state-of-art frequency uncertainties down to the few kilohertz level. We have observed weak intensity resonances unreported so far, resolved subtle doublets never seen before and brought to light discrepancies with the HITRAN database. This demonstrates the potential of our apparatus for probing subtle internal molecular processes, building accurate spectroscopic models of polyatomic molecules of atmospheric or astrophysical interest, and carrying out precise spectroscopic tests of fundamental physics

The Roles and Interactions of Symbiont, Host and Environment in Defining Coral Fitness

Background: Reef-building corals live in symbiosis with a diverse range of dinoflagellate algae (genus Symbiodinium) that differentially influence the fitness of the coral holobiont. The comparative role of symbiont type in holobiont fitness in relation to host genotype or the environment, however, is largely unknown. We addressed this knowledge gap by manipulating host-symbiont combinations and comparing growth, survival and thermal tolerance among the resultant holobionts in different environments.\ud Methodology/Principal Findings: Offspring of the coral, Acropora millepora, from two thermally contrasting locations, were experimentally infected with one of six Symbiodinium types, which spanned three phylogenetic clades (A, C and D), and then outplanted to the two parental field locations (central and southern inshore Great Barrier Reef, Australia). Growth and survival of juvenile corals were monitored for 31–35 weeks, after which their thermo-tolerance was experimentally assessed. Our results showed that: (1) Symbiodinium type was the most important predictor of holobiont fitness, as measured by growth, survival, and thermo-tolerance; (2) growth and survival, but not heat-tolerance, were also affected by local environmental conditions; and (3) host population had little to no effect on holobiont fitness. Furthermore, coral-algal associations were established with symbiont types belonging to clades A, C and D, but three out of four symbiont types belonging to clade C failed to establish a symbiosis. Associations with clade A had the lowest fitness and were unstable in the field. Lastly, Symbiodinium types C1 and D were found to be relatively thermo-tolerant, with type D conferring the highest tolerance in A. millepora.\ud Conclusions/Significance: These results highlight the complex interactions that occur between the coral host, the algal symbiont, and the environment to shape the fitness of the coral holobiont. An improved understanding of the factors affecting coral holobiont fitness will assist in predicting the responses of corals to global climate change

Idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a non-neoplastic pulmonary disease that is characterized by the formation of scar tissue within the lungs in the absence of any known provocation. IPF is a rare disease which affects approximately 5 million persons worldwide. The prevalence is estimated to be slightly greater in men (20.2/100,000) than in women (13.2/100,000). The mean age at presentation is 66 years. IPF initially manifests with symptoms of exercise-induced breathless and dry coughing. Auscultation of the lungs reveals early inspiratory crackles, predominantly located in the lower posterior lung zones upon physical exam. Clubbing is found in approximately 50% of IPF patients. Cor pulmonale develops in association with end-stage disease. In that case, classic signs of right heart failure may be present. Etiology remains incompletely understood. Some environmental factors may be associated with IPF (cigarette smoking, exposure to silica and livestock). IPF is recognized on high-resolution computed tomography by peripheral, subpleural lower lobe reticular opacities in association with subpleural honeycomb changes. IPF is associated with a pathological lesion known as usual interstitial pneumonia (UIP). The UIP pattern consists of normal lung alternating with patches of dense fibrosis, taking the form of collagen sheets. The diagnosis of IPF requires correlation of the clinical setting with radiographic images and a lung biopsy. In the absence of lung biopsy, the diagnosis of IPF can be made by defined clinical criteria that were published in guidelines endorsed by several professional societies. Differential diagnosis includes other idiopathic interstitial pneumonia, connective tissue diseases (systemic sclerosis, polymyositis, rheumatoid arthritis), forme fruste of autoimmune disorders, chronic hypersensitivity pneumonitis and other environmental (sometimes occupational) exposures. IPF is typically progressive and leads to significant disability. The median survival is 2 to 5 years from the time of diagnosis. Medical therapy is ineffective in the treatment of IPF. New molecular therapeutic targets have been identified and several clinical trials are investigating the efficacy of novel medication. Meanwhile, pulmonary transplantation remains a viable option for patients with IPF. It is expected that, during the next decade, considerable progress will be made toward the understanding and treatment of this devastating illness

Coral Uptake of Inorganic Phosphorus and Nitrogen Negatively Affected by Simultaneous Changes in Temperature and pH

The effects of ocean acidification and elevated seawater temperature on coral calcification and photosynthesis have been extensively investigated over the last two decades, whereas they are still unknown on nutrient uptake, despite their importance for coral energetics. We therefore studied the separate and combined impacts of increases in temperature and pCO2 on phosphate, ammonium, and nitrate uptake rates by the scleractinian coral S. pistillata. Three experiments were performed, during 10 days i) at three pHT conditions (8.1, 7.8, and 7.5) and normal temperature (26°C), ii) at three temperature conditions (26°, 29°C, and 33°C) and normal pHT (8.1), and iii) at three pHT conditions (8.1, 7.8, and 7.5) and elevated temperature (33°C). After 10 days of incubation, corals had not bleached, as protein, chlorophyll, and zooxanthellae contents were the same in all treatments. However, photosynthetic rates significantly decreased at 33°C, and were further reduced for the pHT 7.5. The photosynthetic efficiency of PSII was only decreased by elevated temperature. Nutrient uptake rates were not affected by a change in pH alone. Conversely, elevated temperature (33°C) alone induced an increase in phosphate uptake but a severe decrease in nitrate and ammonium uptake rates, even leading to a release of nitrogen into seawater. Combination of high temperature (33°C) and low pHT (7.5) resulted in a significant decrease in phosphate and nitrate uptake rates compared to control corals (26°C, pHT = 8.1). These results indicate that both inorganic nitrogen and phosphorus metabolism may be negatively affected by the cumulative effects of ocean warming and acidification

QTL mapping for brown rot (Monilinia fructigena) resistance in an intraspecific peach (Prunus persica L. Batsch) F1 progeny

Brown rot (BR) caused by Monilinia spp. leads to significant post-harvest losses in stone fruit production, especially peach. Previous genetic analyses in peach progenies suggested that BR resistance segregates as a quantitative trait. In order to uncover genomic regions associated with this trait and identify molecular markers for assisted selection (MAS) in peach, an F1 progeny from the cross "Contender" (C, resistant) 7 "Elegant Lady" (EL, susceptible) was chosen for quantitative trait loci (QTL) analysis. Over two phenotyping seasons, skin (SK) and flesh (FL) artificial infections were performed on fruits using a Monilinia fructigena isolate. For each treatment, infection frequency (if) and average rot diameter (rd) were scored. Significant seasonal and intertrait correlations were found. Maturity date (MD) was significantly correlated with disease impact. Sixty-three simple sequence repeats (SSRs) plus 26 single-nucleotide polymorphism (SNP) markers were used to genotype the C 7 EL population and to construct a linkage map. C 7 EL map included the eight Prunus linkage groups (LG), spanning 572.92 cM, with an average interval distance of 6.9 cM, covering 78.73 % of the peach genome (V1.0). Multiple QTL mapping analysis including MD trait as covariate uncovered three genomic regions associated with BR resistance in the two phenotyping seasons: one containing QTLs for SK resistance traits near M1a (LG C 7 EL-2, R2 = 13.1-31.5 %) and EPPISF032 (LG C 7 EL-4, R2 = 11-14 %) and the others containing QTLs for FL resistance, near markers SNP_IGA_320761 and SNP_IGA_321601 (LG3, R2 = 3.0-11.0 %). These results suggest that in the C 7 EL F1 progeny, skin resistance to fungal penetration and flesh resistance to rot spread are distinguishable mechanisms constituting BR resistance trait, associated with different genomic regions. Discovered QTLs and their associated markers could assist selection of new cultivars with enhanced resistance to Monilinia spp. in fruit