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Variational Inference and Learning of Piecewise-linear Dynamical Systems [article]

Xavier Alameda-Pineda, Vincent Drouard, Radu Horaud
<span title="2020-11-02">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We provide full details of the derivation of two variational expectation-maximization algorithms, a filter and a smoother.  ...  Baseline methods assume that both the dynamic and observation equations follow linear-Gaussian models.  ...  We presented a series of experiments using several datasets. We carried out a benchmark that included our algorithms and several state-of-the-art tracking algorithms.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.01668v2">arXiv:2006.01668v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/udam2tdkg5gvnizvuxm2whqzgi">fatcat:udam2tdkg5gvnizvuxm2whqzgi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201105182629/https://arxiv.org/pdf/2006.01668v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4b/76/4b7688a37dfd131fa5e105e9b2e45d46ecfb6ce6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.01668v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Operator matching during visually aided teleoperation

R.L. Thompson, P.R. McAree, R.W. Daniel, D.W. Murray
<span title="">2005</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ncwahgzkgbfljbalytxadcov3u" style="color: black;">Robotics and Autonomous Systems</a> </i> &nbsp;
via a computer-generated display of the workspace.  ...  Experimental measurements of the times to complete such a task are made, with various degrees of noise added to the pose of objects and different smoothing applied before generating the display.  ...  Acknowledgements This work was supported by Grants GR/L15005 and GR/N03266 from the UK Engineering and Physical Science Research Council.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.robot.2004.10.003">doi:10.1016/j.robot.2004.10.003</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3sbyelaowrefjgt67zm2vdiu5a">fatcat:3sbyelaowrefjgt67zm2vdiu5a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200318164214/http://www.robots.ox.ac.uk/ActiveVision/Publications/thompson_etal_ras2005b/thompson_etal_ras2005b.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/72/4d/724d60f281da518e014d3d0a0726f33b015ac84e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.robot.2004.10.003"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Reconstruction of biomedical images and sparse stochastic modeling

Emrah Bostan, Ulugbek Kamilov, Michael Unser
<span title="">2012</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qcepwfkflvg5toaa6fh2alj3b4" style="color: black;">2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)</a> </i> &nbsp;
While our family of estimators includes the traditional methods of Tikhonov and total-variation (TV) regularization as particular cases, it opens the door to a much broader class of potential functions  ...  We propose a novel statistical formulation of the imagereconstruction problem from noisy linear measurements.  ...  In the experiments, the measurements are corrupted with a Gaussian noise with σ = 10 −4 .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/isbi.2012.6235689">doi:10.1109/isbi.2012.6235689</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/isbi/BostanKU12.html">dblp:conf/isbi/BostanKU12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wffhpjjhxzcwpp3fkp32e6vorm">fatcat:wffhpjjhxzcwpp3fkp32e6vorm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20131015012326/http://bigwww.epfl.ch/publications/bostan1201.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a4/8e/a48ed8240d1c4b997de2dcf3e30ee4d92d033dab.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/isbi.2012.6235689"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

The Description Length of Deep Learning Models [article]

Léonard Blier, Yann Ollivier
<span title="2018-11-01">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The compression viewpoint originally motivated the use of variational methods in neural networks.  ...  Solomonoff's general theory of inference and the Minimum Description Length principle formalize Occam's razor, and hold that a good model of data is a model that is good at losslessly compressing the data  ...  Acknowledgments First, we would like to thank the reviewers for their careful reading and their questions and comments.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.07044v5">arXiv:1802.07044v5</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ievjz22qmbbi5fgiycw5hyhjla">fatcat:ievjz22qmbbi5fgiycw5hyhjla</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200829034703/https://arxiv.org/pdf/1802.07044v5.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a6/01/a6015028e7953c29be6d9e083106b98de2fbfad1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.07044v5" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Multi-output learning via spectral filtering

Luca Baldassarre, Lorenzo Rosasco, Annalisa Barla, Alessandro Verri
<span title="2012-03-28">2012</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h4nnd7sxwzcwhetu5qkjbcdh6u" style="color: black;">Machine Learning</a> </i> &nbsp;
In this paper we study a class of regularized kernel methods for multi-output learning which are based on filtering the spectrum of the kernel matrix.  ...  Finally, we present some promising results of the proposed algorithms on artificial and real data.  ...  Acknowledgements We would like to thank Ernesto De Vito for many useful discussions and the reviewers for their helpful comments.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10994-012-5282-y">doi:10.1007/s10994-012-5282-y</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/f56o5btdkrbhrdoc646yqr6tku">fatcat:f56o5btdkrbhrdoc646yqr6tku</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809194949/http://www0.cs.ucl.ac.uk/staff/l.baldassarre/papers/baldassarre2012multi.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/29/f0/29f0198f00a8eced69665aaff0b3b6e8ce97e26f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10994-012-5282-y"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Book Review

Andrzej Icha
<span title="2018-05-08">2018</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/due6t3xqv5ca3cr34lg4kfqqny" style="color: black;">Pure and Applied Geophysics</a> </i> &nbsp;
These include two main classes of time discretization schemes, namely the explicit and semi-implicit (SI) schemes, and three categories of spatial discretization schemes.  ...  ., reviews the selected temporal and spatial discretization methods, used in numerical weather prediction models (NWP).  ...  The problem how to reduce the uncertainties via model improvement is stated, and two useful measures for Vol. 175, (2018) BookReview 2397 decision making and risk assessments, namely signalto-noise ratio  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00024-018-1893-y">doi:10.1007/s00024-018-1893-y</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mbdijfunrvhtzohtbzkc52r564">fatcat:mbdijfunrvhtzohtbzkc52r564</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190504171414/https://link.springer.com/content/pdf/10.1007%2Fs00024-018-1893-y.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9f/4f/9f4fa9e53f3a708c8232281f990aec699605c7b0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00024-018-1893-y"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Decentralized Variational Filtering for Target Tracking in Binary Sensor Networks

Jing Teng, Hichem Snoussi, Cédric Richard
<span title="">2010</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/m6d55yg2wncgnomdnlvb6ofsmq" style="color: black;">IEEE Transactions on Mobile Computing</a> </i> &nbsp;
Furthermore, since the measurement incorporation and the approximation of the filtering distribution are jointly performed by variational calculus, an effective and lossless compression is achieved.  ...  Second, the variational filtering algorithm is capable of precise tracking even in the highly nonlinear case.  ...  These random variables introduced by the VF act as links that connect the observations to the unknown parameters via Bayes law.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmc.2010.117">doi:10.1109/tmc.2010.117</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gh67uau57zh57geg2n36he263i">fatcat:gh67uau57zh57geg2n36he263i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808221448/http://www.cedric-richard.fr/Articles/teng2010decentralized.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/72/61/72610cd39e7408e699882968f9507299a4ceec30.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmc.2010.117"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

The Asymmetric Business Cycle

James Morley, Jeremy Piger
<span title="">2012</span> <i title="MIT Press - Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s2vfdmfltzhsbomm27f2galmxi" style="color: black;">Review of Economics and Statistics</a> </i> &nbsp;
The model-averaged measure also displays an asymmetric shape and is closely related to other measures of economic slack such as the unemployment rate and capacity utilization.  ...  However, several close competitors to the nonlinear model produce business cycle measures of widely differing shapes and magnitudes.  ...  Because the Kalman filter assumes Gaussian shocks, we do not consider Student t errors for the UC models.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/rest_a_00169">doi:10.1162/rest_a_00169</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6lxosytbdrcwjmbscvhggsez7e">fatcat:6lxosytbdrcwjmbscvhggsez7e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20110411233230/http://research.economics.unsw.edu.au/jmorley/abc.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b0/c2/b0c2d6a8012ed8e6c3bf9050952b99b1d13907a1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/rest_a_00169"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> mitpressjournals.org </button> </a>

Vector autoregression models with skewness and heavy tails [article]

Sune Karlsson, Stepan Mazur, Hoang Nguyen
<span title="2021-05-24">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We propose a general class of generalized hyperbolic skew Student's t distribution with stochastic volatility for the error term in the VAR model that allows us to take into account skewness and heavy  ...  With uncertain changes of the economic environment, macroeconomic downturns during recessions and crises can hardly be explained by a Gaussian structural shock.  ...  The authors acknowledge financial support from the project "Models for macro and financial economics after the financial crisis" (Dnr: P18-0201, BV18-0018) funded by the Jan Wallander and Tom Hedelius  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2105.11182v1">arXiv:2105.11182v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x6a6s5jmwfaj7k5te2nev2b5au">fatcat:x6a6s5jmwfaj7k5te2nev2b5au</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210601182202/https://arxiv.org/pdf/2105.11182v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/96/dc/96dc9148bd5723db1e14728bfafa9b1824470af6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2105.11182v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Priors in Bayesian Deep Learning: A Review [article]

Vincent Fortuin
<span title="2022-03-18">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this review, we highlight the importance of prior choices for Bayesian deep learning and present an overview of different priors that have been proposed for (deep) Gaussian processes, variational autoencoders  ...  , and Bayesian neural networks.  ...  We thank Alex Immer, Adrià Garriga-Alonso, and Claire Vernade for helpful feedback on the draft and Arnold Weber for constant inspiration.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2105.06868v3">arXiv:2105.06868v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dmra3u2ibzgrnblzsepjgrr6pm">fatcat:dmra3u2ibzgrnblzsepjgrr6pm</a> </span>
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Energy-Based Processes for Exchangeable Data [article]

Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
<span title="2020-07-08">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We develop an efficient training procedure for EBPs that demonstrates state-of-the-art performance on a variety of tasks such as point cloud generation, classification, denoising, and image completion.  ...  Acknowledgments We thank Weiyang Liu, Hongge Chen, Adams Wei Yu, and other members of the Google Brain team for helpful discussions.  ...  , neural processes (N Ps) 4 , and variational implicit processes (VIPs) 5 .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.07521v2">arXiv:2003.07521v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4uechnqugrcppkwrjdut5kqaq4">fatcat:4uechnqugrcppkwrjdut5kqaq4</a> </span>
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New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481)

Arthur Gretton, Philipp Hennig, Carl Edward Rasmussen, Bernhard Schölkopf, Marc Herbstritt
<span title="2017-04-12">2017</span> <i title="Schloss Dagstuhl Leibniz-Zentrum für Informatik GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/u2phfyhrhje7xnnubtp3vfklcu" style="color: black;">Dagstuhl Reports</a> </i> &nbsp;
The Dagstuhl Seminar on 16481 "New Directions for Learning with Kernels and Gaussian Processes" brought together two principal theoretical camps of the machine learning community at a crucial time for  ...  Kernel methods and Gaussian process models together form a significant part of the discipline's foundations, but their prominence is waning while more elaborate but poorly understood hierarchical models  ...  Student-t and related processes. Using stochastic processes as inputs to other processes (as in deep GPs) also leads to non-Gaussian processes. 3.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4230/dagrep.6.11.142">doi:10.4230/dagrep.6.11.142</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/journals/dagstuhl-reports/GrettonHRS16.html">dblp:journals/dagstuhl-reports/GrettonHRS16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sky4bixr6fg3djtboe6ueirthi">fatcat:sky4bixr6fg3djtboe6ueirthi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220123034349/https://drops.dagstuhl.de/opus/volltexte/2017/7106/pdf/dagrep_v006_i011_p142_s16481.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/04/67/04672b774732edef727c17965bba764990c7f742.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4230/dagrep.6.11.142"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Background Subtraction with Dirichlet Processes [chapter]

Tom S. F. Haines, Tao Xiang
<span title="">2012</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The Model: Alternative DE methods exist, including different GMM implementations [7] and kernel density estimate (KDE) methods, either using Gaussian kernels [8, 9] or step kernels [10, 7] .  ...  Connected components converts the intermediate foreground mask into regions via pixel adjacency, and culls all regions below a certain size, to remove spurious detections.  ...  Instead of drawing it the Gaussian is integrated out, to give x i ∼ T n i,m , μ i,m , k i,m + 1 k i,m n i,m σ 2 i,m , (3) where T (v, μ, σ 2 ) denotes the three parameter student-t.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-33765-9_8">doi:10.1007/978-3-642-33765-9_8</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eq7eifnvmvcwbd5l7rp24ahyde">fatcat:eq7eifnvmvcwbd5l7rp24ahyde</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170705104132/http://www.eecs.qmul.ac.uk/%7Etxiang/publications/HaniesXiang_ECCV12_background.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ec/db/ecdb30ca14cd1e0fec0370122426db5cf7153815.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-33765-9_8"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges [article]

Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul Fieguth, Xiaochun Cao, Abbas Khosravi, U Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi
<span title="2021-01-06">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Bayesian approximation and ensemble learning techniques are two most widely-used UQ methods in the literature.  ...  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).  ...  [251] proposed a novel technique of variational approximation, termed as Bayes by Hypernet (BbH) that deduced hypernetworks as implicit distributions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.06225v4">arXiv:2011.06225v4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wwnl7duqwbcqbavat225jkns5u">fatcat:wwnl7duqwbcqbavat225jkns5u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210113234503/https://arxiv.org/pdf/2011.06225v4.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f1/4f/f14fc9e399d44463a17cc47a9b339b58f6ef7502.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.06225v4" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Trial-by-trial data analysis using computational models [chapter]

Nathaniel D. Daw
<span title="2011-03-24">2011</span> <i title="Oxford University Press"> Decision Making, Affect, and Learning </i> &nbsp;
I am very grateful to Peter Dayan, John O'Doherty, Yael Niv, Aaron Bornstein, Sam Gershman, Dylan Simon, and Larry Maloney for many helpful conversations about the issues covered here.  ...  A very similar approach is often used in fMRI to capture the (nonlinear) effects of intersubject variation in the hemodynamic response filter .  ...  To produce the BOLD timeseries measured in a voxel, it is assumed that this impulse timeseries is convolved with a hemodynamic response filter, and finally scaled and corrupted by additive Gaussian noise  ... 
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<a target="_blank" rel="noopener" href="https://web.archive.org/web/20100616223912/http://www.cns.nyu.edu/~daw/d10.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/43/c3/43c3d7653710bbb477df108fc2ed2729429d053c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/acprof:oso/9780199600434.003.0001"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> oup.com </button> </a>
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