Academic literature on the topic 'Erreur inverse'
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Journal articles on the topic "Erreur inverse":
ABIAN, ALEXANDER, and PAULA A. KEMP. "THE NATURAL RIGHT AND THE NATURAL LEFT INVERSES OF RECTANGULAR MATRICES." Tamkang Journal of Mathematics 21, no. 3 (December 1, 1990): 279–86. http://dx.doi.org/10.5556/j.tkjm.21.1990.4690.
Iskandar, Fathur Rokhman, Imam Sucahyo, and Meta Yantidewi. "Penerapan Metode Invers kinematik Pada Kontrol Gerak Robot Lengan Tiga Derajat Bebas." Inovasi Fisika Indonesia 9, no. 2 (June 22, 2020): 64–71. http://dx.doi.org/10.26740/ifi.v9n2.p64-71.
Fronczek, Frank R. "The inverse Marsh error." Acta Crystallographica Section A Foundations and Advances 74, a1 (July 20, 2018): a60. http://dx.doi.org/10.1107/s0108767318099397.
Dyer, Justin S., and Stephen A. Dyer. "Approximations to inverse error functions." IEEE Instrumentation & Measurement Magazine 11, no. 5 (October 2008): 32–36. http://dx.doi.org/10.1109/mim.2008.4630740.
Lin, K. C., and P. Lu. "Inverse Simulation - An Error Analysis." SIMULATION 65, no. 6 (December 1995): 385–92. http://dx.doi.org/10.1177/003754979506500602.
Maftuh, Muhammad Hadi. "Lengan Robot Pemindah Barang Berdasarkan Ukuran Tinggi." E-JOINT (Electronica and Electrical Journal Of Innovation Technology) 1, no. 2 (December 27, 2020): 36–41. http://dx.doi.org/10.35970/e-joint.v1i2.431.
Sahoo, Abhilipsa, and Kaushika Patel. "Machine Learning-based Inverse Design Model of a Transistor." Indian Journal Of Science And Technology 17, no. 7 (February 15, 2024): 617–24. http://dx.doi.org/10.17485/ijst/v17i7.3076.
Lopes, Iug, Juliana Maria M. De Melo, and Brauliro Gonçalves Leal. "ESPACIALIZAÇÃO DA TEMPERATURA DO AR PARA A REGIÃO DO SUBMÉDIO SÃO FRANCISCO." IRRIGA 22, no. 1 (June 18, 2018): 177–93. http://dx.doi.org/10.15809/irriga.2017v22n1p177-193.
Wang, P., H. Wang, Y. Q. Wang, X. Y. Zhang, S. L. Gong, M. Xue, C. H. Zhou, et al. "Inverse modeling of black carbon emissions over China using ensemble data assimilation." Atmospheric Chemistry and Physics Discussions 15, no. 15 (August 4, 2015): 20851–79. http://dx.doi.org/10.5194/acpd-15-20851-2015.
Stefanski, Frederik, and Bartosz Minorowicz. "Open loop control of piezoelectric tube transducer." Archives of Mechanical Technology and Materials 38, no. 1 (June 28, 2018): 23–28. http://dx.doi.org/10.2478/amtm-2018-0004.
Dissertations / Theses on the topic "Erreur inverse":
Fu, Shuai. "Inverse problems occurring in uncertainty analysis." Thesis, Paris 11, 2012. http://www.theses.fr/2012PA112208/document.
This thesis provides a probabilistic solution to inverse problems through Bayesian techniques.The inverse problem considered here is to estimate the distribution of a non-observed random variable X from some noisy observed data Y explained by a time-consuming physical model H. In general, such inverse problems are encountered when treating uncertainty in industrial applications. Bayesian inference is favored as it accounts for prior expert knowledge on Xin a small sample size setting. A Metropolis-Hastings-within-Gibbs algorithm is proposed to compute the posterior distribution of the parameters of X through a data augmentation process. Since it requires a high number of calls to the expensive function H, the modelis replaced by a kriging meta-model. This approach involves several errors of different natures and we focus on measuring and reducing the possible impact of those errors. A DAC criterion has been proposed to assess the relevance of the numerical design of experiments and the prior assumption, taking into account the observed data. Another contribution is the construction of adaptive designs of experiments adapted to our particular purpose in the Bayesian framework. The main methodology presented in this thesis has been applied to areal hydraulic engineering case-study
Beuzeville, Theo. "Analyse inverse des erreurs des réseaux de neurones artificiels avec applications aux calculs en virgule flottante et aux attaques adverses." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSEP054.
The use of artificial intelligence, whose implementations are often based on artificial neural networks, is now becoming widespread across a wide variety of tasks. These deep learning models indeed yield much better results than many specialized algorithms previously used and are therefore being deployed on a large scale.It is in this context of very rapid development that issues related to the storage of these models emerge, since they are sometimes very deep and therefore comprise up to billions of parameters, as well as issues related to their computational performance, both in terms of accuracy and time- and energy-related costs. For all these reasons, the use of reduced precision is increasingly being considered.On the other hand, it has been noted that neural networks suffer from a lack of interpretability, given that they are often very deep models trained on vast amounts of data. Consequently, they are highly sensitive to small perturbations in the data they process. Adversarial attacks are an example of this; since these are perturbations often imperceptible to the human eye, constructed to deceive a neural network, causing it to fail in processing the so-called adversarial example.The aim of this thesis is therefore to provide tools to better understand, explain, and predict the sensitivity of artificial neural networks to various types of perturbations.To this end, we first extended to artificial neural networks some well-known concepts from numerical linear algebra, such as condition number and backward error. These quantities allow to better understand the impact of perturbations on a mathematical function or system, depending on which variables are perturbed or not.We then use this backward error analysis to demonstrate how to extend the principle of adversarial attacks to the case where not only the data processed by the networks is perturbed but also their own parameters. This provides a new perspective on neural networks' robustness and allows, for example, to better control quantization to reduce the precision of their storage. We then improved this approach, obtained through backward error analysis, to develop attacks on network input comparable to state-of-the-art methods.Finally, we extended approaches of round-off error analysis, which until now had been approached from a practical standpoint or verified by software, in neural networks by providing a theoretical analysis based on existing work in numerical linear algebra.This analysis allows for obtaining bounds on forward and backward errors when using floating-point arithmetic. These bounds both ensure the proper functioning of neural networks once trained, and provide recommendations on architectures and training methods to enhance the robustness of neural networks
Huang, Shaojuan. "Multi-scale identification of composite materials." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2244/document.
Composite materials are more and more important in the industry community. For the identification of the heterogeneous and anisotropic mechanical behavior of some composite, the full-field measurements are widespread in the mechanics community, because they can offer a very rich information of displacement or strain to exploit heterogeneous tests. During last thirty years, some specific inverse identification strategies have been proposed but most of these methods consider the identification problem only on the measured area and would usually need boundary conditions to be performed. However, the boundary conditions are not always completely known and might not be on the measurement zone. There is hence a need of identification methods allowing both the identification over the whole specimen and the dealing of missing boundary conditions. The Modified Constitutive Relation Error (M-CRE) allows dealing with such situations through the taking into account of the whole available information from a theoretical and experimental point of view without additional assumption. For the identification of elastic properties, a first mono-scale strategy has been proposed and actually used to process different types of boundary conditions as well as their absence. Considering the identification of heterogeneous elastic properties, the lack of information outside the measurement zone prevents from identifying heterogeneous properties in this area. It leads us to propose a multi-scale approach where micro heterogeneous properties are sought at the measurement level and macro homogeneous ones at the specimen level
Barbarella, Elena. "Towards the localization and characterization of defects based on the Modified error in Constitutive Relation : focus on the buckling test and comparison with other type of experiments." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLN066/document.
Composite materials are nowadays extending their operational field to industrial applications other than aeronautics. New potential markets, such as automotive, imply the need to comply with different constraints; reduced cost and production time become more binding, taking the lead over the complete absence of defects. The drawback to fast automatized procedure is the higher defectiveness of the components produced, a deeper control of the part is therefore needed. Non-destructive techniques are expensive both in terms of cost and time and therefore the main question we tried to answer in this thesis is: is it possible to detect and estimate the effect of defects without resorting to the complex and time-consuming NDT techniques? An acceptable answer may potentially lead to a lower precision but should guarantee sufficient quantitative information for these applications. The thesis aims at exploring possibilities to use classical mechanical test combined with Digital Image correlation and inverse procedure to localize and characterized possible (large) defects. Buckling tests have been chosen at first due their supposed sensitivity to defects. Among the possible inverse technique, we have chosen to extend the so-called Modified Error in Constitutive Relation to the case of buckling because, in the case of vibration tests performed with several frequencies, the MCRE proved to have very good localization properties. The dedicated formulation of the MCRE for linearized buckling requires a post-processing of the non-linear experimental results. The Southwell plot is here employed to reconstruct the eigenvalue, the critical load, of the equivalent eigenvalue problem (i.e. the solution of the problem with material defect and no geometrical ones) and the Stereo Digital Image Correlation (StereoDIC) is exploited to reconstruct the deformed shape of the specimen during the test, used as mode. The interests and limits of the methodology are discussed notably through the comparison of numerical results using the MCRE in case of traction, flexion or vibration tests. It is shown that the linearized buckling based MCRE technique proves well for pseudo-experimental measurements at least for moderate geometrical imperfections. In addition first experiments have been performed; the defects are characterized from real experimental specimens, both for a nominally perfect specimen and for a defective one, where a zone of fibre waviness is induced. Stereo Digital Image Correlation (StereoDIC) is exploited to reconstruct the deformed shape of the specimen during the test, this shape being used as an approximation of the buckling mode. While on the first one no defects are detected, on the flawed specimen the localized area is in reasonable agreement with the area affected by fibre undulations
Koohkan, Mohammad Reza. "Multiscale data assimilation approaches and error characterisation applied to the inverse modelling ofatmospheric constituent emission fields." Thesis, Paris Est, 2012. http://www.theses.fr/2012PEST1140/document.
Data assimilation in geophysical sciences aims at optimally estimating the state of the system or some parameters of the system's physical model. To do so, data assimilation needs three types of information: observations and background information, a physical/numerical model, and some statistical description that prescribes uncertainties to each componenent of the system.In my dissertation, new methodologies of data assimilation are used in atmospheric chemistry and physics: the joint use of a 4D-Var with a subgrid statistical model to consistently account for representativeness errors, accounting for multiple scale in the BLUE estimation principle, and a better estimation of prior errors using objective estimation of hyperparameters. These three approaches will be specifically applied to inverse modelling problems focussing on the emission fields of tracers or pollutants. First, in order to estimate the emission inventories of carbon monoxide over France, in-situ stations which are impacted by the representativeness errors are used. A subgrid model is introduced and coupled with a 4D-Var to reduce the representativeness error. Indeed, the results of inverse modelling showed that the 4D-Var routine was not fit to handle the representativeness issues. The coupled data assimilation system led to a much better representation of theCO concentration variability, with a significant improvement of statistical indicators, and more consistent estimation of the CO emission inventory. Second, the evaluation of the potential of the IMS (International Monitoring System) radionuclide network is performed for the inversion of an accidental source. In order to assess the performance of the global network, a multiscale adaptive grid is optimised using a criterion based on degrees of freedom for the signal (DFS). The results show that several specific regions remain poorly observed by the IMS network. Finally, the inversion of the surface fluxes of Volatile Organic Compounds (VOC) are carried out over Western Europe using EMEP stations. The uncertainties of the background values of the emissions, as well as the covariance matrix of the observation errors, are estimated according to the maximum likelihood principle. The prior probability density function of the control parameters is chosen to be Gaussian or semi-normal distributed. Grid-size emission inventories are inverted under these two statistical assumptions. The two kinds of approaches are compared. With the Gaussian assumption, the departure between the posterior and the prior emission inventories is higher than when using the semi-normal assumption, but that method does not provide better scores than the semi-normal in a forecast experiment
Marchand, Basile. "Assimilation de données et recalage rapide de modèles mécaniques complexes." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLN053/document.
For several years, the considerable changes that have occurredin computing tools have led to new practices in the simulation of mechanical structures. Among them, the motivation for this work is the Dynamic Data Driven Application Systems paradigm (DDDAS). The founding idea of this approach is to establish a dialogue between a physical system and its numericalmodel. The objective is then to (i) allow a calibration of the numerical model by means of measurements performed on the physical system; (ii) control the evolution of the physical system using theprediction given by numerical simulation. The major difficulty is to realize this dialogue in real time. This work focuses on the model updating step of the DDDAS paradigm. The problem is then to develop methods and tools to solve inverse problems taking into account various constraints, namely: (i) robustness with respect to corrupted data; (ii) genericity for considering a wide variety of problems and mechanical models; (iii) a reduced computation time in order to tend towards a real-time model updating.The starting point of this work is the modified Constitutive Relation Error, an energetic approach dedicated to the solution of inverse problems in mechanics, notably illustrated by its robustness with respect to measurement noises. First, in order to guarantee a fast identification process, we have coupled the modified Constitutive Relation Error with the PGD model reduction in the linear model framework, thus enabling a fast and automatic identification process. Then, in order to be applied to the DDDAS paradigm, we have developed an identification method based on a data assimilation process (the Kalman filter) and using the modified Constitutive Relation Error as an observer alwayswithin the framework of linear problems. We have then extended this data assimilation approach to the problem of the identification of parameter fields by introducing a separation of the spatial discretizations and by introducing tools resulting from the mesh adaptation framework. We have then addressed the problem of non-linear mechanical models, through damage and visco-plasticitymodels. To this end, we have first recast and extended the concept of the modified Constitutive Relation Error to this nonlinear material framework and we have implemented a dedicated resolution process, based on the LaTIn method. Finally, we have introduced this reformulation of the modified Constitutive Relation Error in the previously data assimilation method in order to process the model updating of nonlinear models
Ben, Azzouna Mouldi. "Identification à partir de mesures de champs : application de l'erreur en relation de comportement modifiée." Phd thesis, Université de Technologie de Compiègne, 2013. http://tel.archives-ouvertes.fr/tel-00968138.
Casanove, Marie-José. "Deconvolution partielle et reconstruction d'image : un nouveau principe de regularisation." Toulouse 3, 1987. http://www.theses.fr/1987TOU30022.
Nouisri, Amine. "Identification paramétrique en dynamique transitoire : traitement d’un problème couplé aux deux bouts." Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLN005/document.
This thesis deals with parameters identification in transient dynamic in case of highly noisy experimental data. One long-term goal is the derivation of a non-intrusive method dedicated to the implementation in a commercial finite element code.In this work, the modified error in the constitutive relation framework is used to treat the identification of material parameters. The minimization of the cost function under constraints leads, in the case of transient dynamics, to a « two points boundary value problem » in which the differential space-time problem involves both initial and final time conditions. This results in a problem coupling the direct and adjoint fields, whose treatment is difficult.In the first part, methods such as those based on the « Riccati equations » and the « shooting methods » have been studied. It is shown that the identification is robust even in the case of highly corrupted measures, but these methods are limited either by the implementation intrusiveness, conditioning problems or the numerical cost.In the second part, an iterative over-relaxation approach is developed and compared to the aforementioned approaches on academic problems in order to validate the interest of the method. Finally, comparisons are carried out between this approach and a « discretized » variation of the formulation introduced by Bonnet and Aquino [Inverse Problems, vol. 31, 2015]
Khazâal, Ali. "Reconstruction d'images pour la mission spatiale SMOS." Toulouse 3, 2009. http://thesesups.ups-tlse.fr/917/.
Synthetic aperture imaging radiometers are powerful sensors for high-resolution observations of the Earth at low microwave frequencies. Within this context, the European Space Agency is currently developing the Soil Moisture and Ocean Salinity (SMOS) mission devoted to the monitoring of SMOS at global scale from L-band space-borne radiometric observations obtained with a 2-D interferometer. This PhD is concerned with the reconstruction of radiometric brightness temperature maps from interferometric measurements through a regularization approach called Band Limited Regularization. More exactly, it concerns with the reduction of the systematic error (or bias) in the reconstruction of radiometric brightness temperature maps from SMOS interferometric measurements. It also extends the concept of "band-limited regularization approach" to the case of the processing of dual and full polarimetric data. Also, two problems that may affect the quality of the reconstruction are investigated. First, the impact of correlators and receivers failures on the reconstruction process is studied. Then, the calibration of MIRAS antenna's voltage patterns, when the instrument is in orbit, is also studied where a general approach is proposed to estimate this antenna's patterns
Books on the topic "Erreur inverse":
Nelson, P. A. MINT, the multiple error LMS algorithm, and the design of inverse filters for multi-channel sound reproduction systems. Southampton, England: University of Southampton, 1992.
Ammari, Habib. Imaging, multi-scale, and high-contrast partial differential equations: Seoul ICM 2014 Satellite Conference, August 7-9, 2014, Daejeon, Korea. Providence, Rhode Island: American Mathematical Society, 2016.
Desiere, Sam, and Dean Jolliffe. Land Productivity and Plot Size: Is Measurement Error Driving the Inverse Relationship? Elsevier, 2017. http://dx.doi.org/10.1596/28786.
Desiere, Sam, and Dean Jolliffe. Land Productivity and Plot Size: Is Measurement Error Driving the Inverse Relationship? World Bank, Washington, DC, 2017. http://dx.doi.org/10.1596/1813-9450-8134.
McCleary, Richard, David McDowall, and Bradley J. Bartos. Statistical Conclusion Validity. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190661557.003.0006.
Hernández, Carlos. Positivismo inclusivo. Universidad Libre sede principal, 2017. http://dx.doi.org/10.18041/978-958-8981-73-4.
Book chapters on the topic "Erreur inverse":
Yagola, Anatoly G., and Yury M. Korolev. "Error Estimation in Ill-Posed Problems in Special Cases." In Applied Inverse Problems, 155–64. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7816-4_9.
Koshev, N., and L. Beilina. "A Posteriori Error Estimates for Fredholm Integral Equations of the First Kind." In Applied Inverse Problems, 75–93. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7816-4_5.
Barba, Paolo Di. "Inverse Problems and Error Minimisation." In Lecture Notes in Electrical Engineering, 5–25. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3080-1_2.
Malmberg, John Bondestam. "A Posteriori Error Estimate in the Lagrangian Setting for an Inverse Problem Based on a New Formulation of Maxwell’s System." In Inverse Problems and Applications, 43–53. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12499-5_3.
Kaveh, M., and M. Soumekh. "Algorithms and Error Analysis for Diffraction Tomography Using the Born and Rytov Approximations." In Inverse Methods in Electromagnetic Imaging, 1137–46. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5271-3_25.
Kaveh, M., and M. Soumekh. "Algorithms and Error Analysis for Diffraction Tomography Using the Born and Rytov Approximations." In Inverse Methods in Electromagnetic Imaging, 1137–46. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-010-9444-3_64.
Bernstein, Daniel J., and Tanja Lange. "Inverted Edwards Coordinates." In Applied Algebra, Algebraic Algorithms and Error-Correcting Codes, 20–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-77224-8_4.
Łoś, Marcin, Robert Schaefer, and Maciej Smołka. "Effective Solution of Ill-Posed Inverse Problems with Stabilized Forward Solver." In Computational Science – ICCS 2021, 343–57. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77964-1_27.
Wiesbeck, W. "A Complete Error Model for Polarimetric RCS- and Antenna Measurements." In Direct and Inverse Methods in Radar Polarimetry, 793–807. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-010-9243-2_29.
Carvalho, Francisco, and João Tiago Mexia. "Inference in Error Orthogonal Models." In Combinatorial Matrix Theory and Generalized Inverses of Matrices, 85–100. India: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1053-5_8.
Conference papers on the topic "Erreur inverse":
Lee, Kyeong Ha, Seung Guk Baek, and Ja Choon Koo. "Real-Time High Bandwidth Feedforward Position Control of Electro-Hydraulic Actuator Using Non-Minimum Phase Inverse Model." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67628.
CHENG, JIN, XIANZHENG JIA, and YANBO WANG. "NUMERICAL DIFFERENTIATION ON THE NONUNIFORM GRID AND ITS ERROR ESTIMATE." In Proceedings of the International Conference on Inverse Problems. WORLD SCIENTIFIC, 2003. http://dx.doi.org/10.1142/9789812704924_0020.
Ting, Kwun-Lon, Kuan-Lun Hsu, Long-Iong Wu, and Jun Wang. "A Modular Method for Manufacturing Error Analysis of Linkages and Manipulators." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-68163.
Arnon, Gal, Alessandro Chiesa, and Eylon Yogev. "IOPs with Inverse Polynomial Soundness Error." In 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2023. http://dx.doi.org/10.1109/focs57990.2023.00050.
Li, C. James, and Hyeongceol Shin. "Tracking Bearing Spall Severity Through Inverse Modeling." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60851.
Javani, Mohammad H., Mohammadreza Zandehshahvar, Muliang Zhu, Tyler Brown, Yashar Kiarashi, and Ali Adibi. "Inverse Design of Nanophotonics Structures with Minimal Computation Using a Pruning Approach." In CLEO: Applications and Technology. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/cleo_at.2022.jw3b.132.
Kubo, Shiro, and Kiyotsugu Ohji. "Estimation of Distributions of Contact Stressess and Displacements Using Regularization Schemes." In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0219.
Morovati, Vahid, Hamid Mohammadi, and Roozbeh Dargazany. "A Generalized Approach to Improve Approximation of Inverse Langevin Function." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-88228.
Saad, Joseph, and Matthias Liermann. "Inverse Dynamic Simulation of a Hydraulic Drive With Modelica." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-63310.
Sinha, Anirban, and Nilanjan Chakraborty. "Computing Robust Inverse Kinematics Under Uncertainty." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97945.
Reports on the topic "Erreur inverse":
Rodi, William L. Error Analysis in the Joint Event Location/Seismic Calibration Inverse Problem. Fort Belvoir, VA: Defense Technical Information Center, February 2008. http://dx.doi.org/10.21236/ada479709.
Rintoul, Mark Daniel, Elebeoba Eni May, William Michael Brown, Anna Marie Johnston, and Jean-Paul Watson. Deciphering the genetic regulatory code using an inverse error control coding framework. Office of Scientific and Technical Information (OSTI), March 2005. http://dx.doi.org/10.2172/922758.
Hughett, P. Tradeoffs between measurement residual and reconstruction error in inverse problems with prior information. Office of Scientific and Technical Information (OSTI), June 1995. http://dx.doi.org/10.2172/106621.
Kott, Phillip S. The Role of Weights in Regression Modeling and Imputation. RTI Press, April 2022. http://dx.doi.org/10.3768/rtipress.2022.mr.0047.2203.
Kaffenberger, Michelle, and Lant Pritchett. Women’s Education May Be Even Better Than We Thought: Estimating the Gains from Education When Schooling Ain’t Learning. Research on Improving Systems of Education (RISE), September 2020. http://dx.doi.org/10.35489/bsg-rise-wp_2020/049.