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A review of uncertainty quantification in deep learning: Techniques, applications and challenges
2021
Information Fusion
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This study reviews recent advances in UQ methods used in deep learning, investigates the application of these methods in reinforcement learning, and highlights fundamental research challenges and directions ...
Bayesian approximation and ensemble learning techniques are two widely-used types of uncertainty quantification (UQ) methods. ...
[310] presented an uncertainty-aware consistency regularization technique for cross-domain semantic segmentation. ...
doi:10.1016/j.inffus.2021.05.008
fatcat:yschhguyxbfntftj6jv4dgywxm
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
[article]
2021
arXiv
pre-print
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This study reviews recent advances in UQ methods used in deep learning. Moreover, we also investigate the application of these methods in reinforcement learning (RL). ...
Bayesian approximation and ensemble learning techniques are two most widely-used UQ methods in the literature. ...
[513] introduced an uncertainty-aware domain alignment approach to tackle the domain shift issue in the cross-domain UDA (Unsupervised Domain Adaptation) task. ...
arXiv:2011.06225v4
fatcat:wwnl7duqwbcqbavat225jkns5u
Deep Reinforcement Learning
[article]
2018
arXiv
pre-print
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Then we discuss important mechanisms for RL, including attention and memory, unsupervised learning, hierarchical RL, multi-agent RL, relational RL, and learning to learn. ...
We start with background of artificial intelligence, machine learning, deep learning, and reinforcement learning (RL), with resources. ...
Lanctot et al. (2017) observe that independent RL, in which each agent learns by interacting with the environment, oblivious to other agents, can overfit the learned policies to other agents' policies ...
arXiv:1810.06339v1
fatcat:kp7atz5pdbeqta352e6b3nmuhy
Data Science Competence Framework (Cf-Ds): Approach And Working Version
2016
Zenodo
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, and for companies to better define a set of required competences and skills for their specific industry domain in their search for Data Science talents, on the other hand. ...
CF-DS will provide a basis for Data Science Body of Knowledge (DS-BoK) and Model Curriculum (MC-DC) definitions, and further for the Data Science Professional certification. ...
stakeholders, primarily from research community and Research Infrastructures, but also involving industry via standardisation bodies, professional communities and directly via the project network. ...
doi:10.5281/zenodo.159438
fatcat:iq3ce3ygzbfvpmfgnxwyduappa
Edison Data Science Framework: Part 3. Data Science Model Curriculum (Mc-Ds) Release 2
2017
Zenodo
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When coupled with individual or group competence benchmarking, MC-DS can also be used for building individual training curricula and professional (self/up) skilling for effective career management. ...
The MC-DS is built based on CF-DS and DS-BoK, where Learning Outcomes are defined based on CF-DS competences and Learning Units are mapped to Knowledge Units in DS-BoK. ...
technology,
algorithms, tools (including supervised,
unsupervised, or reinforced learning)
Level 3
SDSDA05
Apply Prescriptive Analytics
methods
Level 3
Cooperate with the CEN TC428 and ...
doi:10.5281/zenodo.1044357
fatcat:g5k7jybupfcexnd4a74vacanry
Edison Data Science Framework: Part 1. Data Science Competence Framework (Cf-Ds) Release 2
2017
Zenodo
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, and for companies to better define a set of required competences and skills for their specific industry domain in their search for Data Science talents, on the other hand. ...
The EDISON project is designed to create a foundation for establishing a new profession of Data Scientist for European research and industry. ...
and directly via the project network. ...
doi:10.5281/zenodo.1044345
fatcat:ybg432e6lfhgboplyo22ka37ci
Pedestrian Models for Autonomous Driving Part II: high level models of human behaviour
[article]
2020
arXiv
pre-print
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At these levels, early work has been done on descriptive and qualitative models of behaviour, but much work is still needed to translate them into quantitative algorithms for practical AV control. ...
Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on high-streets ...
It is found that elderly people have a preference for road facilities that they consider to be safer such as pavements, pedestrian crossings, signalized intersections, cycle paths. ...
arXiv:2003.11959v1
fatcat:acjjwohahvdlxgy56j45fjtkdq
PUNCH4NFDI Consortium Proposal
2020
Zenodo
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that offers all storage and compute opportunities and all data transformation possibilities required for making the data fully productive in a sustainable way. ...
Organised in 7 task areas, the consortium ultimately aims at establishing FAIR digital research products for its communities and beyond, spending their entire lifecycle inside a "science data platform" ...
Those tools often provide alternative functionality to existing domain-specific solutions, but are often not yet validated for use with domain-specific data. ...
doi:10.5281/zenodo.5722894
fatcat:mfcvk55kqvgsthkp6dnxqyiyve
Engineering, Technology & Applied Science Research (ETASR), Vol. 11, No. 2, pp. 6845-7068
[article]
2021
Zenodo
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The table of contents for this issue can be found at: https://etasr.com/index.php/ETASR/issue/view/68. For more info visit the journal's site at: www.etasr.com. ...
Engineering, Technology & Applied Science Research (ETASR) is an international bimonthly wide scope, peer-reviewed open access journal for the publication of original articles concerned with diverse aspects ...
Afef Hammami, director of the AFA center, and all its members for their cooperation in creating the AD dataset from Arabic voices. ...
doi:10.5281/zenodo.4720665
fatcat:mk2prflstjaa3bhkjenwy22s6u
25th Annual Computational Neuroscience Meeting: CNS-2016
2016
BMC Neuroscience
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I will discuss theoretical results that point to functional advantages of splitting neural populations into subtypes, both in feedforward and recurrent networks. ...
BMC Neuroscience 2016, 17(Suppl 1):A1 Neural circuits are notorious for the complexity of their organization. ...
Allen and Jody Allen, for their vision, encouragement and support. ...
doi:10.1186/s12868-016-0283-6
pmid:27534393
pmcid:PMC5001212
fatcat:bt45etzj2bbolfcxlxo7hlv6ju
a need to know
1983
Physician and sportsmedicine
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Using
Unsupervised Learning Methods for Matching
Nonprobability Samples to Probability Sample-
FTrent Buskirk, Marketing Systems Group; David
Dutwin, SSRS
11:55 a.m. ...
Learning Network Dynamics via Regularized
Tensor Decomposition-FYun-Jhong Wu,
University of Michigan; Elizaveta Levina,
University of Michigan; Ji Zhu, University of
Michigan
9:35 a.m. ...
Help SOI celebrate its centennial by visiting www.irs.gov/taxstats, learning more about the U.S. tax system, and supporting SOI's work as it prepares for the next 100 years. 192 Allen, Genevera 88, 93 ...
doi:10.1080/00913847.1983.11708423
pmid:27409254
fatcat:7rlbreoerngb3epmighz7l5vr4
An Introduction to Probabilistic Programming
[article]
2021
arXiv
pre-print
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We then discuss gradient-based maximum likelihood estimation in programs that are parameterized using neural networks, how to amortize inference using by learning neural approximations to the program posterior ...
Foundational algorithms for this kind of language are discussed in the context of an interface between program executions and an inference controller. ...
Most critically, while all of the authors were at Oxford together, three of them were explicitly supported at various times by the DARPA under its Probabilistic Programming for Advanced Machine Learning ...
arXiv:1809.10756v2
fatcat:cdcsscxbu5af7fpm5w6mjjiyra
Welcome Messages
2019
2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
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The database would be very useful to carry out deep learning research and various image processing tasks. ...
The database along with its source code will be made open source for the research and academic purpose. ...
CROSS CONDITIONAL NETWORK FOR SPEECH ENHANCEMENT We show the proposed network architecture in the Fig. 1 . The generator consists of two symmetric autoencoders. ...
doi:10.1109/ispacs48206.2019.8986291
fatcat:gu4zaxsqkncp5n2ebj5fybk7ce
Modeling the 3D Milky Way using Machine Learning with Gaia and infrared surveys
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:2010.01431v1 fatcat:o6qchcvdhrdsvfjhl746axok2u
In a second part, I will propose a new method for reconstructing the 3D extinction distribution of the MW based on Convolutional Neural Networks (CNN). ...
Concurrently, the past two decades have seen an explosion of the use of Machine Learning (ML) methods that are also increasingly employed in astronomy. ...
There are obviously plenty of other frameworks that we did not describe here like Caffe, Theano, MXNET, scikit-learn (very suitable for teaching), etc. ...
arXiv:2010.01431v2
fatcat:pd7w4q3nijdp5mrxozon2z3mmq
Patient-generated evidence in Epidermolysis Bullosa (EB): Development of a questionnaire to assess the Quality of Life
[chapter]
2021
Proceedings e report
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As a result of this disorder, patients face an unbearable burden in their lives, and their Quality of Life (QoL) is negatively affected at every life cycle stage. ...
The methodological process to develop the questionnaire consisted of two phases: firstly, a critical review of scientific literature was performed; secondly, a pseudo-Delphi study was carried out. ...
We acknowledge anonymous reviewer for the fruitful comments. ...
doi:10.36253/978-88-5518-461-8.38
fatcat:2yp72egbhrcvxng7avqoskbpse
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