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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1970 1
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2006 2
2007 1
2009 1
2011 2
2012 2
2013 4
2014 4
2015 6
2016 9
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2019 14
2020 13
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2024 6

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Page 1
Automated Model Inference for Gaussian Processes: An Overview of State-of-the-Art Methods and Algorithms.
Berns F, Hüwel J, Beecks C. Berns F, et al. SN Comput Sci. 2022;3(4):300. doi: 10.1007/s42979-022-01186-x. Epub 2022 May 21. SN Comput Sci. 2022. PMID: 35647556 Free PMC article. Review.
While the latter approximation relies on representing data via local sub-models, global approaches capture data's inherent characteristics by means of an educated sample. In this paper, we investigate the current state-of-the-art in automated model inference for Gaussian p …
While the latter approximation relies on representing data via local sub-models, global approaches capture data's inherent characteristics b …
Machine learning used for simulation of MitraClip intervention: A proof-of-concept study.
Dabiri Y, Mahadevan VS, Guccione JM, Kassab GS. Dabiri Y, et al. Front Genet. 2023 Mar 9;14:1142446. doi: 10.3389/fgene.2023.1142446. eCollection 2023. Front Genet. 2023. PMID: 36968590 Free PMC article.
Although finite element (FE) modeling can simulate the outcomes of different MC scenarios, it is not suitable for clinical usage because it requires several hours to complete. Methods: In this paper, we used machine learning (ML) to predict the outcomes of MC therapy in le …
Although finite element (FE) modeling can simulate the outcomes of different MC scenarios, it is not suitable for clinical usage because it …
Guaranteed State Estimation Using a Bundle of Interval Observers with Adaptive Gains Applied to the Induction Machine.
Schwartz M, Krebs S, Hohmann S. Schwartz M, et al. Sensors (Basel). 2021 Apr 7;21(8):2584. doi: 10.3390/s21082584. Sensors (Basel). 2021. PMID: 33917007 Free PMC article.
The scope of this paper is the design of an interval observer bundle for the guaranteed state estimation of an uncertain induction machine with linear, time-varying dynamics. ...One advantage of such an interval observer bundle is the possibility to reinitialize the …
The scope of this paper is the design of an interval observer bundle for the guaranteed state estimation of an uncertain induction …
Rapid runtime learning by curating small datasets of high-quality items obtained from memory.
German JS, Cui G, Xu C, Jacobs RA. German JS, et al. PLoS Comput Biol. 2023 Oct 4;19(10):e1011445. doi: 10.1371/journal.pcbi.1011445. eCollection 2023 Oct. PLoS Comput Biol. 2023. PMID: 37792896 Free PMC article.
We propose the "runtime learning" hypothesis which states that people quickly learn to perform unfamiliar tasks as the tasks arise by using task-relevant instances of concepts stored in memory during mental training. ...The paper motivates the hypothesis by describi …
We propose the "runtime learning" hypothesis which states that people quickly learn to perform unfamiliar tasks as the tasks a …
A Survey of Crypto Ransomware Attack Detection Methodologies: An Evolving Outlook.
Alqahtani A, Sheldon FT. Alqahtani A, et al. Sensors (Basel). 2022 Feb 25;22(5):1837. doi: 10.3390/s22051837. Sensors (Basel). 2022. PMID: 35270983 Free PMC article. Review.
Due to its unique characteristics, ransomware has attracted the attention of security professionals and researchers toward achieving safer and higher assurance systems that can effectively detect and prevent such attacks. The state-of-the-art crypto ransomware early detect …
Due to its unique characteristics, ransomware has attracted the attention of security professionals and researchers toward achieving safer a …
Fast Hierarchical Games for Image Explanations.
Teneggi J, Luster A, Sulam J. Teneggi J, et al. IEEE Trans Pattern Anal Mach Intell. 2023 Apr;45(4):4494-4503. doi: 10.1109/TPAMI.2022.3189849. Epub 2023 Mar 7. IEEE Trans Pattern Anal Mach Intell. 2023. PMID: 35816535
The current lack of interpretability often undermines the deployment of accurate machine learning tools in sensitive settings. In this work, we present a model-agnostic explanation method for image classification based on a hierarchical extension of Shapley coefficients-Hi …
The current lack of interpretability often undermines the deployment of accurate machine learning tools in sensitive settings. In thi …
Discovering faster matrix multiplication algorithms with reinforcement learning.
Fawzi A, Balog M, Huang A, Hubert T, Romera-Paredes B, Barekatain M, Novikov A, R Ruiz FJ, Schrittwieser J, Swirszcz G, Silver D, Hassabis D, Kohli P. Fawzi A, et al. Nature. 2022 Oct;610(7930):47-53. doi: 10.1038/s41586-022-05172-4. Epub 2022 Oct 5. Nature. 2022. PMID: 36198780 Free PMC article.
Matrix multiplication is one such primitive task, occurring in many systems-from neural networks to scientific computing routines. The automatic discovery of algorithms using machine learning offers the prospect of reaching beyond human intuition and outperforming the curr …
Matrix multiplication is one such primitive task, occurring in many systems-from neural networks to scientific computing routines. The autom …
MSC: a metagenomic sequence classification algorithm.
Saha S, Johnson J, Pal S, Weinstock GM, Rajasekaran S. Saha S, et al. Bioinformatics. 2019 Sep 1;35(17):2932-2940. doi: 10.1093/bioinformatics/bty1071. Bioinformatics. 2019. PMID: 30649204 Free PMC article.
Since such a collection of reference genomes is very large, the approach often needs high-end computing machines with large memory which is not often available to researchers. ...MSC is primarily designed to detect prevalence and experimental results show that MSC is indee …
Since such a collection of reference genomes is very large, the approach often needs high-end computing machines with large memory wh …
Yin-Yang: Programming Abstractions for Cross-Domain Multi-Acceleration.
Kim JK, Ahn BH, Kinzer S, Ghodrati S, Mahapatra R, Yatham B, Wang ST, Kim D, Sarikhani P, Mahmoudi B, Mahajan D, Park J, Esmaeilzadeh H. Kim JK, et al. IEEE Micro. 2022 Sep-Oct;42(5):89-98. doi: 10.1109/mm.2022.3189416. Epub 2022 Aug 1. IEEE Micro. 2022. PMID: 37008678 Free PMC article.
The Yin abstraction enables cross-domain algorithmic specification, while the Yang abstraction captures the accelerator capabilities. We also develop a dataflow virtual machine, dubbed XLVM, that transparently maps domain functions (Yin) to best-fit accelerator capabilitie …
The Yin abstraction enables cross-domain algorithmic specification, while the Yang abstraction captures the accelerator capabilities. We als …
CARE 2.0: reducing false-positive sequencing error corrections using machine learning.
Kallenborn F, Cascitti J, Schmidt B. Kallenborn F, et al. BMC Bioinformatics. 2022 Jun 13;23(1):227. doi: 10.1186/s12859-022-04754-3. BMC Bioinformatics. 2022. PMID: 35698033 Free PMC article.
On a simulated full human dataset with 914M reads CARE 2.0 generates only 1.2M false positives (FPs) (and 801.4M true positives (TPs)) at a highly competitive runtime while the best corrections achieved by other state-of-the-art tools contain at least 3.9M FPs and a …
On a simulated full human dataset with 914M reads CARE 2.0 generates only 1.2M false positives (FPs) (and 801.4M true positives (TPs)) at a …
128 results