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295 results for “Approximation”
Predicting parameters for the Quantum Approximate OptimizationAlgorithm for MAX-CUT from the infinite-size limit
<p>This is the raw data used to generate the figures of the paper. The code generating the figures is in a separate GitHub repository: https://github.com/sami-b95/predicting_qaoa_parameters_data</p>
FIGURE 2. Approximate distribution maps for species from 11 in Systematics of the blindsnakes (Serpentes: Scolecophidia: Typhlopoidea) based on molecular and morphological evidence
FIGURE 2. Approximate distribution maps for species from 11 of 19 typhlopoid genera; Amerotyphlops, Xenotyphlopidae (Xenotyphlops), Gerrhopilidae (Gerrhopilus), Typhlops, Rhinotyphlops, Anilios, Xerotyphlops, Indotyphlops, Madatyphlops, Argyrophis, and Malayotyphlops. Seven other genera are pictured in Figure 4. Note that I. braminus has an essentially cosmopolitan distribution, and is not factored into the range for Indotyphlops (see Wallach 2009 for a recent summary of known localities).
FIGURE 3. Approximate distribution maps for species from 7 in Systematics of the blindsnakes (Serpentes: Scolecophidia: Typhlopoidea) based on molecular and morphological evidence
FIGURE 3. Approximate distribution maps for species from 7 of 19 typhlopoid genera: Grypotyphlops, Letheobia, Lemuriatyphlops, Cyclotyphlops, Acutotyphlops, Afrotyphlops, and Ramphotyphlops.
Error curves of finite completely monotonic functions associated with inverse power functions by exponential sum approximations
<p>Each figure of page <span class="math-tex">\(M=1,\ldots,17\)</span> in each PDF file represents the error curve of a finite completely monotonic function <span class="math-tex">\(f(x) = \int_a^b \mathrm{e}^{-xt} \frac{t^{\eta - 1}}{\Gamma(\eta)} \mathrm{d}t\)</span> by an <span class="math-tex">\(M\)</span>-term exponential sum approximation. Each PDF file corresponds to the following parameters:</p> <p>inverse_power0.5_a0.5_b1_EMx.pdf for <span class="math-tex">\(\eta = 0.5, a = 2^{-1}, b = 1\)</span><br> inverse_power0.5_a0.0009765625_b1_EMx.pdf for <span class="math-tex">\(\eta = 0.5, a = 2^{-10}, b = 1\)</span><br> inverse_power1_a0.5_b1_EMx.pdf for <span class="math-tex">\(\eta = 1, a = 2^{-1}, b = 1\)</span><br> inverse_power1_a0.0009765625_b1_EMx.pdf for <span class="math-tex">\(\eta = 1, a = 2^{-10}, b = 1\)</span><br> inverse_power2_a0.5_b1_EMx.pdf for <span class="math-tex">\(\eta = 2, a = 2^{-1}, b = 1\)</span><br> inverse_power2_a0.0009765625_b1_EMx.pdf for <span class="math-tex">\(\eta = 2, a = 2^{-10}, b = 1\)</span></p> <p> </p> <p>Each page includes 6 row figures:<br> Row=1 Best exponential sum approximation<br> Row=2 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\Phi_{a/b}(u)\)</span><br> Row=3 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\varphi_{\exp, a/b}(u)\)</span><br> Row=4 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\varphi_{\mathcal{P}_2, a/b}(u)\)</span><br> Row=5 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\varphi_{\mathcal{P}_1, a/b}(u)\)</span><br> Row=6 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\varphi_{\mathcal{R}_{0, 1}, a/b}(u)\)</span></p> <p> </p> <p>The figures were generated by</p> <p>https://github.com/ymkoyama/fcmf, commit 17342bf3974eee9b4d6b3d21b06f13b87929a85b on January 21, 2023.</p>
Supplementary dataset for paper: "Approximate non-linear model predictive control with safety-augmented neural networks"
<p>Supplementary dataset for paper Henrik Hose and Johannes Koehler and Melanie N. Zeilinger and Sebastian Trimpe "Approximate non-linear model predictive control with safety-augmented neural networks".</p> <p>The code to use this dataset is publicly available at <a href="https://github.com/hshose/soeampc">https://github.com/hshose/soeampc</a></p> <p>The dataset contains training and testing data to train an NN controller for three standard benchmark systems, a stir tank reactor, a quadcopter, and a chain mass system.</p> <p>For each system, there are initial conditions as comma separated value in the `x0.txt` file, the MPC input trajectory in the `U.txt` file and the corresponding predicted state sequence in the `X.txt` file. MPC parameters are provided for each system. The dataset was computed using acados for SQP solving.</p> <p>The dataset also contains pretrained neural network approximations of the dataset.These are provided in the `pretrained_models.zip` file. The neural networks were trained with tensorflow.</p>
Effects of AbClo Fascial Approximation Device in Patients With Open Abdomen on Respiratory Mechanics
ClinicalTrials.gov study NCT07154589. IPD Sharing: NO. Countries: 1. Publications: 11.
Evaluate Immune Response Approximately 5 to 6 Years After Receiving Different Formulations of GSK Bio Hep B Vaccine
ClinicalTrials.gov study NCT00329576. IPD Sharing: YES. Countries: 3. Publications: 1.
Cost-effective Analysis of Two Approximation Devices in Closure of Gastrointestinal Defects
ClinicalTrials.gov study NCT05163665. IPD Sharing: Not stated. Countries: 1. Publications: 1.
CONTRAST (Can cONTrast Injection Better Approximate FFR compAred to Pure reSTing Physiology?)
ClinicalTrials.gov study NCT02184117. IPD Sharing: Not stated. Countries: 9. Publications: 15.
The Effect of Rectus Muscle Re-approximation at Cesarean Delivery on Postoperative Pain
ClinicalTrials.gov study NCT05260970. IPD Sharing: NO. Countries: 1. Publications: 0.
Effect of Curodont Repair in Patients With Early Approximal Carious Lesions
ClinicalTrials.gov study NCT02119507. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Laparoscopic Primary Umbilical Hernia Repair With Routine Defect Closure Using Su2ura Approximation Device
ClinicalTrials.gov study NCT04393532. IPD Sharing: NO. Countries: 2. Publications: 14.
Cardiovascular Disease CVD Constitutes a Significant Health Challenge for Individuals With Type 2 Diabetes Mellitus T2DM, Affecting Approximately 32% of This Population and Contributing Significantly
ClinicalTrials.gov study NCT07204782. IPD Sharing: NO. Countries: 1. Publications: 3.
Weight Approximation in Stroke Before Thrombolysis
ClinicalTrials.gov study NCT01006434. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effect of Curodont™ Repair in Patients With Early Approximal Carious Lesions
ClinicalTrials.gov study NCT02101255. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Reconstructing the demographic history of orang-utans using approximate Bayesian computation
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Data from: Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates
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Data from: Understanding the recent colonization history of a plant pathogenic fungus using population genetic tools and Approximate Bayesian Computation
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Data from: Approximate Bayesian computation analysis of EST-associated microsatellites indicates that the broadleaved evergreen tree Castanopsis sieboldii survived the Last Glacial Maximum in multiple refugia in Japan
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Data from: Assessing conservation risks to populations of an anadromous Arctic salmonid, the northern Dolly Varden (Salvelinus malma malma), via estimates of effective and census population sizes and approximate Bayesian computation
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.