Sun Planet Interactions Digital Environment on Request (SPIDER) for Europlanet RI H2024

2020 ◽  
Author(s):  
Nicolas André ◽  
Vincent Génot ◽  
Andrea Opitz ◽  
Baptiste Cecconi ◽  
Nick Achilleos ◽  
...  
Keyword(s):  
Solar Wind ◽  
Giant Planet ◽  
High Energy ◽  
Research Infrastructure ◽  
Radiation Environment ◽  
High Energy Particle ◽  
Particle Tracing ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Infrastructure Project

<p>The H2020 Europlanet-2020 programme, which ended on Aug 31<sup>st</sup>, 2019, included an activity called PSWS (Planetary Space Weather Services), which provided 12 services distributed over four different domains (A. Prediction, B. Detection, C. Modelling, D. Alerts) and accessed through the PSWS portal (http://planetaryspaceweather-europlanet.irap.omp.eu/):</p> <p>A1. 1D MHD Solar Wind Prediction Tool – HELIOPROPA,</p> <p>A2. Propagation Tool,</p> <p>A3. Meteor showers,</p> <p>A4. Cometary tail crossings – TAILCATCHER,</p> <p>B1. Lunar impacts – ALFIE,</p> <p>B2. Giant planet fireballs – DeTeCt3.1,</p> <p>B3. Cometary tails – WINDSOCKS,</p> <p>C1. Earth, Mars, Venus, Jupiter coupling- TRANSPLANET,</p> <p>C2. Mars radiation environment – RADMAREE,</p> <p>C3. Giant planet magnetodiscs – MAGNETODISC,</p> <p>C4. Jupiter’s thermosphere, D. Alerts.</p> <p>In the framework of the starting Europlanet-2024 programme, SPIDER will extend PSWS domains (A. Prediction, C. Modelling, E. Databases) services and give the European planetary scientists, space agencies and industries access to 6 unique, publicly available and sophisticated services in order to model planetary environments and solar wind interactions through the deployment of a dedicated run on request infrastructure and associated databases.</p> <p>C5. A service for runs on request of models of Jupiter’s moon exospheres as well as the exosphere of Mercury,</p> <p>C6. A service to connect the open-source Spacecraft-Plasma Interaction Software (SPIS) software with models of space environments in order to compute the effect of spacecraft potential on scientific instruments onboard space missions. Pre-configured simulations will be made for Bepi-Colombo and JUICE missions,</p> <p>C7. A service for runs on request of particle tracing models in planetary magnetospheres,</p> <p>E1. A database of the high-energy particle flux proxy at Mars, Venus and comet 67P using background counts observed in the data obtained by the plasma instruments onboard Mars Express (operational from 2003), Venus Express (2006–2014), and Rosetta (2014–2015);</p> <p>E2. A simulation database for Mercury and Jupiter’s moons magnetospheres and link them with prediction of the solar wind parameters from Europlanet-RI H2020 PSWS services.</p> <p>A1. An extension of the Europlanet-RI H2020 PSWS Heliopropa service in order to ingest new observations from Solar missions like the ESA Solar Orbiter or NASA Solar Parker Probe missions and use them as input parameters for solar wind prediction;</p> <p>These developments will be discussed in the presentation.</p> <p>The Europlanet 2020 Research Infrastructure project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 654208.</p> <p>The Europlanet 2024 Research Infrastructure project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149.</p>

Sun Planet Interactions Digital Environment on Request (VESPASPIDER) for Europlanet RI H2024: status after 2 years

2021 ◽  
Author(s):  
Nicolas André ◽  
Team Spider
Keyword(s):  
Solar Wind ◽  
Giant Planet ◽  
High Energy ◽  
Radiation Environment ◽  
High Energy Particle ◽  
Particle Tracing ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Cometary Tail ◽  
Space Environments

<p>The H2020 Europlanet-2020 programme, which ended on Aug 31<sup>st</sup>, 2019, included an activity called PSWS (Planetary Space Weather Services), which provided 12 services distributed over four different domains (A. Prediction, B. Detection, C. Modelling, D. Alerts) and accessed through the PSWS portal (http://planetaryspaceweather-europlanet.irap.omp.eu/):</p> <p>A1. 1D MHD Solar Wind Prediction Tool – HELIOPROPA,</p> <p>A2. Propagation Tool,</p> <p>A3. Meteor showers,</p> <p>A4. Cometary tail crossings – TAILCATCHER,</p> <p>B1. Lunar impacts – ALFIE,</p> <p>B2. Giant planet fireballs – DeTeCt3.1,</p> <p>B3. Cometary tails – WINDSOCKS,</p> <p>C1. Earth, Mars, Venus, Jupiter coupling- TRANSPLANET,</p> <p>C2. Mars radiation environment – RADMAREE,</p> <p>C3. Giant planet magnetodiscs – MAGNETODISC,</p> <p>C4. Jupiter’s thermosphere, D. Alerts.</p> <p>In the framework of the ongoing Europlanet-2024 programme, SPIDER will extend PSWS domains (A. Prediction, C. Modelling, E. Databases) services and give the European planetary scientists, space agencies and industries access to 6 unique, publicly available and sophisticated services in order to model planetary environments and solar wind interactions through the deployment of a dedicated run on request infrastructure and associated databases.</p> <p>C5. A service for runs on request of models of Jupiter’s moon exospheres as well as the exosphere of Mercury,</p> <p>C6. A service to connect the open-source Spacecraft-Plasma Interaction Software (SPIS) software with models of space environments in order to compute the effect of spacecraft potential on scientific instruments onboard space missions. Pre-configured simulations will be made for Bepi-Colombo and JUICE missions,</p> <p>C7. A service for runs on request of particle tracing models in planetary magnetospheres,</p> <p>E1. A database of the high-energy particle flux proxy at Mars, Venus and comet 67P using background counts observed in the data obtained by the plasma instruments onboard Mars Express (operational from 2003), Venus Express (2006–2014), and Rosetta (2014–2015);</p> <p>E2. A simulation database for Mercury and Jupiter’s moons magnetospheres and link them with prediction of the solar wind parameters from Europlanet-RI H2020 PSWS services.</p> <p>A1. An extension of the Europlanet-RI H2020 PSWS Heliopropa service in order to ingest new observations from Solar missions like the ESA Solar Orbiter or NASA Solar Parker Probe missions and use them as input parameters for solar wind prediction;</p> <p>The developments performed during the second year of the project will be discussed in the presentation.</p> <p>The Europlanet 2020 Research Infrastructure project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 654208.</p>

Improving CME evolution and arrival predictions with AMR and grid stretching in EUHFORIA

2021 ◽  
Author(s):  
Tinatin Baratashvili ◽  
Christine Verbeke ◽  
Nicolas Wijsen ◽  
Emmanuel Chané ◽  
Stefaan Poedts
Keyword(s):  
Solar Wind ◽  
Adaptive Mesh Refinement ◽  
Adaptive Mesh ◽  
Mhd Equations ◽  
Efficiency Gain ◽  
The European Union ◽  
Interplanetary Shocks ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Speed Up

<p>Coronal Mass Ejections (CMEs) are the main drivers of interplanetary shocks and space weather disturbances. Strong CMEs directed towards Earth can cause severe damage to our planet. Predicting the arrival time and impact of such CMEs can enable to mitigate the damage on various technological systems on Earth. </p><p>We model the inner heliospheric solar wind and the CME propagation and evolution within a new heliospheric model based on the MPI-AMRVAC code. It is crucial for such a numerical tool to be highly optimized and efficient, in order to produce timely forecasts. Our model solves the ideal MHD equations to obtain a steady state solar wind configuration in a reference frame corotating with the Sun. In addition, CMEs can be modelled by injecting a cone CME from the inner boundary (0.1 AU).</p><p>Advanced techniques, such as grid stretching and Adaptive Mesh Refinement (AMR) are employed in the simulation. Such methods allow for high(er) spatial resolution in the numerical domain, but only where necessary or wanted. As a result, we can obtain a detailed, highly resolved image at the (propagating) shock areas, without refining the whole domain.</p><p>These techniques guarantee more efficient simulations, resulting in optimised computer memory usage and a significant speed-up. The obtained speed-up, compared to the original approach with a high-resolution grid everywhere, varies between a factor of 45 - 100 depending on the domain configuration. Such efficiency gain is momentous for the mitigation of the possible damage and allows for multiple simulations with different input parameters configurations to account for the uncertainties in the measurements to determine them. The goal of the project is to reproduce the observed results, therefore, the observable variables, such as speed, density, etc., are compared to the same type of results produced by the existing (non-stretched, single grid) EUropean Heliospheric FORecasting Information Asset (EUHFORIA) model and observational data for a particular event on 12th of July, 2012. The shock features are analyzed and the results produced with the new heliospheric model are in agreement with the existing model and observations, but with a significantly better performance. </p><p> </p><p><strong>This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0).</strong></p>

Modeling the Sun – Earth propagation of solar disturbances for the H2020 SafeSpace project

2021 ◽  
Author(s):  
Benoit Lavraud ◽  
Rui Pinto ◽  
Rungployphan Kieokaew ◽  
Evangelia Samara ◽  
Stefaan Poedts ◽  
...  
Keyword(s):  
Solar Wind ◽  
Interplanetary Space ◽  
Coronal Magnetic Field ◽  
Physical Parameters ◽  
The European Union ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Reconstruction Methods ◽  
Solar Disturbances ◽  
Magnetic Field Computation

<p>We present the solar wind forecast pipeline that is being implemented as part of the H2020 SafeSpace project. The Goal of this project is to use several tools in a modular fashion to address the physics of Sun – interplanetary space – Earth’s magnetosphere. This presentation focuses on the part of the pipeline that is dedicated to the forecasting – from solar measurements – of the solar wind properties at the Lagrangian L1 point. The modeling pipeline puts together different mature research models: determination of the background coronal magnetic field, computation of solar wind acceleration profiles (1 to 90 solar radii), propagation across the heliosphere (for regular solar wind, CIRs and CMEs), and comparison to spacecraft measurements. Different magnetogram sources (WSO, SOLIS, GONG, ADAPT) can be combined, as well as coronal field reconstruction methods (PFSS, NLFFF), wind (MULTI-VP) and heliospheric propagation models (CDPP 1D MHD, EUHFORIA). We aim at providing a web-based service that continuously supplies a full set of bulk physical parameters of the solar wind at 1 AU several days in advance, at a time cadence compatible with space weather applications. This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437.</p>

Radiation Shielding Analysis for Various Materials in the Extreme Jovian Environment

2006 ◽  
Vol 929 ◽  
Author(s):  
William Atwell
Keyword(s):  
Radiation Effects ◽  
Absorbed Dose ◽  
High Energy ◽  
Radiation Shielding ◽  
Radiation Environment ◽  
High Energy Particle ◽  
Dose Calculations ◽  
Environment Model ◽  
Computer Codes ◽  
Trapped Radiation

ABSTRACTEarlier particle experiments in the 1970s on Pioneer-10 and -11 and Voyager-1 and -2 provided Jupiter flyby particle data, which were used by Divine and Garrett to develop the first Jupiter trapped radiation environment model. This model was used to establish a baseline radiation effects design limit for the Galileo onboard electronics. Recently, Garrett et al. have developed an updated Galileo Interim Radiation Environment (GIRE) model based on Galileo electron data. In this paper, the GIRE model was utilized to generate trapped proton and electron spectra as a function of Rj (Rj = radius of Jupiter = ∼71,400 km). Using these spectra and a high-energy particle transport codes (MCNPX and HZETRN), radiation exposures and dose effects for a variety of shielding materials (Al, polyethylene [PE], and Ta plus several other elemental materials for “Graded-Z” portion of the paper) and thicknesses are presented for the Icy Moon, Europa, Ganymede, and Callisto for several orbital inclinations. In addition, an in-depth discussion and absorbed dose calculations are presented for “Graded-Z” materials and several computer codes were utilized for comparison purposes. We find overall there is generally quite good agreement between the various computer codes utilized in the study: MCNPX (Monte Carlo) vs. HZETRN (deterministic) for slab shielding and the comparison of “Graded-Z” shielding using the CEPXS, NOVICE, and NASA JPL codes. Finally, we conclude that the merits of using “Graded-Z” materials that include PE, due to cost and weight, should aid future Jupiter mission planners and spacecraft designers.

scholarly journals EuPRAXIA Conceptual Design Report

2020 ◽  
Vol 229 (24) ◽  
pp. 3675-4284
Author(s):  
R. W. Assmann ◽  
M. K. Weikum ◽  
T. Akhter ◽  
D. Alesini ◽  
A. S. Alexandrova ◽  
...  
Keyword(s):  
Conceptual Design ◽  
High Energy Physics ◽  
Gamma Ray ◽  
Knowledge Exchange ◽  
High Energy ◽  
Particle Accelerator ◽  
Research Infrastructure ◽  
The European Union ◽  
Horizon 2020 ◽  
Energy Frontier

AbstractThis report presents the conceptual design of a new European research infrastructure EuPRAXIA. The concept has been established over the last four years in a unique collaboration of 41 laboratories within a Horizon 2020 design study funded by the European Union. EuPRAXIA is the first European project that develops a dedicated particle accelerator research infrastructure based on novel plasma acceleration concepts and laser technology. It focuses on the development of electron accelerators and underlying technologies, their user communities, and the exploitation of existing accelerator infrastructures in Europe. EuPRAXIA has involved, amongst others, the international laser community and industry to build links and bridges with accelerator science — through realising synergies, identifying disruptive ideas, innovating, and fostering knowledge exchange. The Eu-PRAXIA project aims at the construction of an innovative electron accelerator using laser- and electron-beam-driven plasma wakefield acceleration that offers a significant reduction in size and possible savings in cost over current state-of-the-art radiofrequency-based accelerators. The foreseen electron energy range of one to five gigaelectronvolts (GeV) and its performance goals will enable versatile applications in various domains, e.g. as a compact free-electron laser (FEL), compact sources for medical imaging and positron generation, table-top test beams for particle detectors, as well as deeply penetrating X-ray and gamma-ray sources for material testing. EuPRAXIA is designed to be the required stepping stone to possible future plasma-based facilities, such as linear colliders at the high-energy physics (HEP) energy frontier. Consistent with a high-confidence approach, the project includes measures to retire risk by establishing scaled technology demonstrators. This report includes preliminary models for project implementation, cost and schedule that would allow operation of the full Eu-PRAXIA facility within 8—10 years.

scholarly journals Energy Poverty and Protection of Vulnerable Consumers. Overview of the EU Funding Programs FP7 and H2020 and Future Trends in Horizon Europe

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1030 ◽  
Author(s):  
Danila Longo ◽  
Giulia Olivieri ◽  
Rossella Roversi ◽  
Giulia Turci ◽  
Beatrice Turillazzi
Keyword(s):  
Social Inclusion ◽  
Well Being ◽  
High Energy ◽  
Urban Systems ◽  
Energy Prices ◽  
Energy Poverty ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Residential Energy Efficiency ◽  
The Eu

Energy poverty—involving a combination of factors, such as low household incomes, high energy prices, and low levels of residential energy efficiency—is identified as a complex and increasing issue affecting people’s physical health, well-being, and social inclusion. Even though a shared identification of energy poverty is not yet agreed, this phenomenon has been recognized as an EU priority. Several EU legislative documents address the topic, trying to outline its boundaries and provide a framework for mitigative actions. At the same time, different research and demonstration projects have been funded to experiment and evaluate innovative approaches, strategies, and solutions and to promote good practices at national, regional, and local levels. This review paper presents some results of the “ZOOM” project (“Energy zoning for urban systems. Models and relations for the built environment”, funded by University of Bologna in the framework of Alma Idea 2017–ongoing), proposing a critical overview of the EU projects directly or indirectly connected to energy poverty—funded under the 7th Framework Program (FP7) and under Horizon 2020 Program (H2020). The aim of such a review is to highlight the main objectives, trends, and related topics of ongoing and concluded projects addressing energy poverty, in order to identify gaps and open issues and to understand the possible orientation and placement of this subject in the future EU research and innovation framework project, Horizon Europe.

scholarly journals A self-consistent simulation of proton acceleration and transport near a high-speed solar wind stream

2021 ◽  
Author(s):  
Nicolas Wijsen ◽  
Evangelia Samara ◽  
Àngels Aran ◽  
David Lario ◽  
Jens Pomoell ◽  
...  
Keyword(s):  
Solar Wind ◽  
Energetic Particle ◽  
High Speed ◽  
Three Dimensional ◽  
Acceleration Process ◽  
Solar Wind Stream ◽  
The European Union ◽  
Horizon 2020 ◽  
Compression Waves ◽  
Research And Innovation

<p>Solar wind stream interaction regions (SIRs)  are often characterised by energetic ion enhancements. The mechanisms accelerating these particles as well as the locations where the acceleration occurs, remains debated. Here, we report the findings of a simulation of a SIR-event observed by Parker Solar Probe at 0.56 au and the Solar Terrestrial Relations Observatory-Ahead at 0.96 au in September 2019 when both spacecraft were approximately radially aligned with the Sun. The simulation reproduces the solar wind configuration and the energetic particle enhancements observed by both spacecraft. Our results show that the energetic particles are produced at the compression waves associated with the SIR and that the suprathermal tail of the solar wind is a good candidate to provide the seed population for particle acceleration. The simulation confirms that the acceleration process does not require shock waves and can already commence within Earth's orbit, with an energy dependence on the precise location where particles are accelerated. The three-dimensional configuration  of the solar wind streams strongly modulates the energetic particle distributions, illustrating the necessity of advanced models to understand  these particle events.</p><p>This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0).</p><p> </p>

The Dynamic Time Warping as a means to assess modeled solar wind time series

2021 ◽  
Author(s):  
Evangelia Samara ◽  
Emmanuel Chane ◽  
Brecht Laperre ◽  
Christine Verbeke ◽  
Manuela Temmer ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Wind ◽  
Dynamic Time Warping ◽  
Optimal Alignment ◽  
The European Union ◽  
Time Warping ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Single Number ◽  
Dynamic Time

<p>In this work, the Dynamic Time Warping (DTW) technique is presented as an alternative method to assess the performance of modeled solar wind time series at Earth (or at any other point in the heliosphere). This method can quantify how similar two time series are by providing a temporal alignment between them, in an optimal way and under certain restrictions. It eventually estimates the optimal alignment between an observed and a modeled series, which we call the warping path, by providing a single number, the so-called DTW cost. A description on the reasons why DTW should be applied as a metric for the assessment of solar wind time series, is presented. Furthermore, examples on how exactly the technique is applied to our modeled solar wind datasets with EUHFORIA, are shown and discussed.</p><p><span><span><em>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437 (SafeSpace).</em></span></span></p>

Mercury’s exospheric model for SPIDER

2021 ◽  
Author(s):  
Martina Moroni ◽  
Alessandro Mura ◽  
Anna Milillo ◽  
Andrè Nicolas
Keyword(s):  
Solar Wind ◽  
Solar System ◽  
Three Dimensional ◽  
Numerical Data ◽  
Release Mechanism ◽  
Three Dimensional Model ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Area Of Interest ◽  
Loss Mechanisms

<div> <p><span>The propagation of Solar events and the response of planetary environment is a fundamental area of interest in the study of the solar system, object of several models and tools for data analysis. In the framework of the starting Europlanet-2024 program, the Virtual Activity (VA) SPIDER (Sun-Planet Interactions Digital Environment on Request) aims a publicly available and sophisticated services, in order to model planetary environments and solar wind interactions. One of these services is focused on the prototype for the model of the Mercury exosphere, in particular to study its exospheric density and the solar wind precipitation to the surface. Mercury is a unique case in the solar system: absence of an atmosphere and the weakness of the intrinsic magnetic field. The Hermean exosphere is continuously eroded and refilled by interactions with plasma and surface, so the environment is considered as a single, unified system – surface- exosphere-magnetosphere</span><span>.  </span><span>The study of the generation mechanisms, the compositions and the configuration of the Hermean exosphere will provide crucial insight in the planet status and evolution.</span></p> </div><div> <p><span>The MESSENGER/NASA mission visited Mercury in the period 2008-2015, adding a consistent amount of data but a global description of planet’s exosphere is still not available; the ESA BepiColombo mission will study Mercury orbiting around the planet from 2025. For this reason, it is important to have a modelling tool ready for interpreting observational data and testing different hypothesis on release mechanism.  Considering different generation and loss mechanisms</span><span>, </span><span>we present a Monte Carlo three-dimensional model of the Hermean exosphere, that considers all the major sources and loss mechanisms. In fact, this numerical model includes among the processes responsible of the formation of such an exosphere the ion sputtering (IS), the thermal desorption (TD), the photon-stimulated desorption (PSD) and micro-meteoroids impact vaporization (MMIV) from the planetary surface. The model calculates the trajectories of ejected particles from which we obtain the spatial and energy distributions of atmospheric particles. Furthermore, an analytical model is obtained by fitting the numerical data with parametric functions. In this way, it is possible to model the exosphere of Mercury for each source separately and we can investigate the role of each physical source independently of the others.  </span></p> </div><div> <p><span>Here we present the web-based interface of the model and the functionalities of this infrastructure that is being implemented in SPIDER. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149.</span></p> </div>

scholarly journals Unsupervised Solar Wind Classification Using Wavelet Variational Autoencoders and Self-Organazing Maps

2021 ◽  
Author(s):  
Jorge Amaya ◽  
Sara Jamal ◽  
Giovanni Lapenta
Keyword(s):  
Solar Wind ◽  
Single Point ◽  
Coronal Holes ◽  
Principal Component ◽  
Data Transformation ◽  
Unsupervised Classification ◽  
Kernel Principal Component Analysis ◽  
Horizon 2020 ◽  
Research And Innovation

<p>Last year we published an automatic method for the automatic classification of the solar wind [1]. We showed that data transformation and unsupervised clustering can be used to classify observations made by the ACE spacecraft. Two data transformation techniques were used: Kernel Principal Component Analysis (KPCA) and Auto-encoder Neural Networks. After data transformation three clustering techniques were tested: k-means, Bayesian Gaussian Mixtures (BGM), and Self-Organizing Maps (SOM). Although the results were very positive we ran into a few difficulties: a) the data from the ACE mission contains a very small population of observations originated at high latitude coronal holes, b) the measured features contain a high degree of intercorrelation, c) the data distribution is compact in the feature space, and d) the final algorithm produces a single categorical class for a single point in time.</p><p><br>In this work we present an improvement of the model that redresses some of the limitations above. We are still making use of the two main features of our previous work, i.e. the data transformation using auto-encoders and the unsupervised classification using SOM. But in the present work: a) we include the analysis of Ulysses data with observations of the solar wind originated at high latitudes; b) we perform a Factor Analysis to reduce the number of features used as inputs; c) we transform windows of time of the multi-variate time series (instead of instantaneous observations) into scalograms using wavelet transformations; d) we apply the variational version of the auto-encoder [2] to parametrize the scalograms; f) we finally use the SOM to automatically classify the windows of time in different categories.</p><p><br>This method can be adapted to the classification of observations from the Parker Solar Probe and Solar Orbiter missions.</p><p><br>The work presented in this abstract has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 754304 (DEEP-EST, www.deep-projects.eu), and from the European Union's Horizon 2020 research and innovation programme under grant agreement No 776262 (AIDA, www.aida-space.eu).</p><p><br>[1] Amaya, Jorge, Romain Dupuis, Maria Elena Innocenti, and Giovanni Lapenta. "Visualizing and Interpreting Unsupervised Solar Wind Classifications." arXiv preprint arXiv:2004.13430 (2020).</p><p>[2] Kingma, Diederik P., and Max Welling. "Auto-encoding variational bayes." arXiv preprint arXiv:1312.6114 (2013).</p>

Sign in / Sign up

Export Citation Format

Share Document