A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Filters
Towards realistic market simulations
2021
Proceedings of the Second ACM International Conference on AI in Finance
Preserved Fulltext
To addresses this challenge we propose a synthetic market generator based on Conditional Generative Adversarial Networks (CGANs) trained on real aggregate-level historical data. ...
Backtesting, a widely used approach, consists of simulating experimental strategies while replaying historical market scenarios. ...
We study the following stylized facts: • Generative Adversarial Networks (GANs). ...
doi:10.1145/3490354.3494411
fatcat:gugdew4qpza6xkxer4yelllype
Towards Realistic Market Simulations: a Generative Adversarial Networks Approach
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
To addresses this challenge we propose a synthetic market generator based on Conditional Generative Adversarial Networks (CGANs) trained on real aggregate-level historical data. ...
Backtesting, a widely used approach, consists of simulating experimental strategies while replaying historical market scenarios. ...
Generative Adversarial Networks (GANs). ...
arXiv:2110.13287v1
fatcat:mpinu24movdnhlibaefljyyrvm
Modern ICT Network Simulator for Co-Simulations in Smart Grid Applications
2022
International Conference on Cyber Warfare and Security (ICIW)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
It also demonstrates our simulators capabilities to perform real-world ICT attacks on realistic network topologies. ...
The current transformation of power grids towards smart grids and the associated increase in the use of ICT technologies lead to an increased attack surface via the communication network. ...
New approaches and concepts can thus be tested as in a realistic environment, even before the rollout on actual hardware. ...
doi:10.34190/iccws.17.1.44
fatcat:qatjwuqz7bgnteaehraynowzmi
Training robust anomaly detection using ML-Enhanced simulations
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Our approach enhances simulations using neural networks trained on real-world data to create outputs that are more realistic and variable than traditional simulations. ...
This paper describes the use of neural networks to enhance simulations for subsequent training of anomaly-detection systems. ...
Noise Training and Generation In this approach, noise is trained independently using Generative Adversarial Neural Networks (GANs) Generative adversarial learning is a technique where a generative network ...
arXiv:2008.12082v2
fatcat:gapu4zh3gnhzzdjfsgplb4obsu
Systematic review of features for co‐simulating security incidents in Cyber‐Physical Systems
2021
Security and Privacy
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Addressing security requires developing modeling and simulation tools that approximate and replicate adversarial behavior in the SG. ...
The technique of composing two models of computation in a global simulation of these coupled systems is called co-simulation. ...
The authors implemented a Smart Grid Simulator for experimentation and validation of the approach in a realistic case study. ...
doi:10.1002/spy2.150
fatcat:mcrafuc2tnbqnmsywuniygcbcq
Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
within an optimization framework to tune parameters of a simulator model with known agent archetypes to represent a market scenario. ...
In this paper, we address the problem of multi-agent simulator parameter calibration to allow simulator capture characteristics of different market regimes. ...
Figure 9 : 9 Generative adversarial network architecture with self-attention.
Figure 10 : 10 Generative adversarial network architecture without self-attention (used for the ablation study). ...
arXiv:2108.00664v1
fatcat:xeilvnj7afhqhhvd4peffsjgfy
Privacy assessment in vehicular networks using simulation
2014
Proceedings of the Winter Simulation Conference 2014
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
While vehicular network algorithms are usually evaluated by means of simulation, it is a non-trivial task to assess the performance of a privacy protection mechanism. ...
Vehicular networks are envisioned to play an important role in the building of intelligent transportation systems. ...
We conducted a systematic literature review concerning the assessment of privacy in simulations of vehicular networks. ...
doi:10.1109/wsc.2014.7020152
dblp:conf/wsc/WagnerE14
fatcat:mmmlfpuf7jcd7p6p63f3ysmu6i
MASS: Mobile Autonomous Station Simulation
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Traces are generated by a user- and context-aware trained generative adversarial network (GAN). ...
Our results show that we beat both traditional statistical distribution fitting approaches as well as a state-of-the-art GAN time series generator across these metrics. ...
Adversarial architecture of MassGAN Like all GAN models, MassGAN also has a generator network and a discriminator network. ...
arXiv:2111.09161v1
fatcat:3hkbicxavff57hoh4hzviyjury
Modeling multiple communities of interest for interactive simulation and gaming: the dynamic adversarial gaming algorithm project
2007
Modeling and Simulation for Military Operations II
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The Dynamic Adversarial Gaming Algorithm (DAGA) project aims to provide a wargaming environment for automation of simulating dynamics of geopolitical crisis and eventually be applied to military simulation ...
In this paper, we describe our COI modeling, the development of cultural networks, the interaction architecture, and a prototype of DAGA. ...
A realistic adversarial simulation beyond simply modeling attrition principles requires a system capability for predicting with continual assessment of the intentions and courses of actions of all parties ...
doi:10.1117/12.722319
fatcat:avz6sxt5q5eerlxqc2stxy36aq
A Data-driven Market Simulator for Small Data Environments
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We also contrast some classical approaches of market simulation with simulation based on generative modelling and highlight some advantages and pitfalls of the new approach. ...
Neural network based data-driven market simulation unveils a new and flexible way of modelling financial time series without imposing assumptions on the underlying stochastic dynamics. ...
The emergence of DNN-based financial applications is one of the driving factors that directed the interest towards highly realistic market simulators: A key factor for training these deep networks to a ...
arXiv:2006.14498v1
fatcat:imtmblo64jgr5gp2xfcbneac3y
Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Components
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We present a testing framework that is compatible with test case generation and automatic falsification methods, which are used to evaluate cyber-physical systems. ...
One of the main challenges is that many autonomous driving systems have machine learning components, such as deep neural networks, for which formal properties are difficult to characterize. ...
Under this category, we could also potentially include generative adversarial networks [13] . ...
arXiv:1804.06760v4
fatcat:jxy5mrzrjjhvferrzm7jltncne
An Attack Simulation and Evidence Chains Generation Model for Critical Information Infrastructures
2022
Electronics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
., log files, which are evidence of cyber-attacks on a system or network. ...
This paper proposes an attack simulation and evidence chains generation model which computes all possible attack paths associated with specific, confirmed security events. ...
simulation and evidence chains generation approach. ...
doi:10.3390/electronics11030404
fatcat:fs4o3ruzezg5npw5ijmy2uucci
Technological Heterogeneity and Path Diversity in Smart Home Resilience: A Simulation Approach
2020
Procedia Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Our approach involves simulating and modeling the interaction of diverse smart home technologies in the context of their relationship to the core internet. ...
Our approach involves simulating and modeling the interaction of diverse smart home technologies in the context of their relationship to the core internet. ...
In order to do that, we generate a number of flows from various nodes in the network toward Server/Cloud node. ...
doi:10.1016/j.procs.2020.03.023
fatcat:iijpxfixvrgnlajxf3b6tfffmm
Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
New hybrid, data-centric engineering approaches, leveraging the best of both worlds and integrating both simulations and data, are emerging as a powerful tool with a transformative impact on the physical ...
Mechanistic models, based on physical equations, and purely data-driven statistical approaches represent two ends of the modelling spectrum. ...
Generative modelling and simulations Deep generative models, which include variational autoencoders and generative adversarial networks (GANs) have been hugely successful in generating realistic synthetic ...
arXiv:2111.06223v2
fatcat:ejwhon6envhandje4twvatgliq
Sim4CV: A Photo-Realistic Simulator for Computer Vision Applications
2018
International Journal of Computer Vision
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We present a photo-realistic training and evaluation simulator (Sim4CV) with extensive applications across various fields of computer vision. ...
The simulator fully integrates both several state-of-the-art tracking algorithms with a benchmark evaluation tool and a deep neural network (DNN) architecture for training vehicles to drive autonomously ...
The differences in appearance between the simulated and real-world will need to be reconciled through deep transfer learning techniques (e.g. generative adversarial networks) to enable a smooth transition ...
doi:10.1007/s11263-018-1073-7
fatcat:go2kohdljzfmfemp5z536p2qhy
« Previous
Showing results 1 — 15 out of 4,894 results