activity
20172022
most citedA survey on Variational Autoencoders from a GreenAI perspective

5 citations · 7 across the 4 of their papers we have counts for

collaborators

6 papers

q-fin.TR20221 cited

Price formation in financial markets: a game-theoretic perspective

David Evangelista, Yuri Saporito, Yuri Thamsten

We propose two novel frameworks to study the price formation of an asset negotiated in an order book. Specifically, we develop a game-theoretic model in many-person games and mean-…

math.NA2022

RISING a new framework for few-view tomographic image reconstruction with deep learning

Davide Evangelista, Elena Morotti, Elena Loli Piccolomini

This paper proposes a new two-step procedure for sparse-view tomographic image reconstruction. It is called RISING, since it combines an early-stopped Rapid Iterative Solver with a…

cs.LG20215 cited

A survey on Variational Autoencoders from a GreenAI perspective

A. Asperti, D. Evangelista, E. Loli Piccolomini

Variational AutoEncoders (VAEs) are powerful generative models that merge elements from statistics and information theory with the flexibility offered by deep neural networks to ef…

q-fin.MF2020

On finite population games of optimal trading

David Evangelista, Yuri Thamsten

We investigate stochastic differential games of optimal trading comprising a finite population. There are market frictions in the present framework, which take the form of stochast…

q-fin.TR2018

Optimal inventory management and order book modeling

Nicolas Baradel, Bruno Bouchard, David Evangelista +1

We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) fir…

math.AP20171 cited

Radially Symmetric Mean-Field Games with Congestion

David Evangelista, Diogo A. Gomes, Levon Nurbekyan

Here, we study radial solutions for first- and second-order stationary Mean-Field Games (MFG) with congestion on . MFGs with congestion model problems where the agent…