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Learning who is in the market from time series: market participant
  discovery through adversarial calibration of multi-agent simulators

Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators

2 August 2021
Victor Storchan
Svitlana Vyetrenko
T. Balch
ArXivPDFHTML

Papers citing "Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators"

4 / 4 papers shown
Title
Deep Calibration of Market Simulations using Neural Density Estimators
  and Embedding Networks
Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks
Namid R Stillman
R. Baggott
Justin Lyon
Jianfei Zhang
Dingqui Zhu
Tao Chen
Perukrishnen Vytelingum
27
1
0
20 Nov 2023
INTAGS: Interactive Agent-Guided Simulation
INTAGS: Interactive Agent-Guided Simulation
Song Wei
Andrea Coletta
Svitlana Vyetrenko
T. Balch
24
1
0
04 Sep 2023
Efficient Calibration of Multi-Agent Simulation Models from Output
  Series with Bayesian Optimization
Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization
Yuanlu Bai
Henry Lam
Svitlana Vyetrenko
T. Balch
27
10
0
03 Dec 2021
SDE approximations of GANs training and its long-run behavior
SDE approximations of GANs training and its long-run behavior
Haoyang Cao
Xin Guo
31
1
0
03 Jun 2020
1