Tootfinder

"If workers are discontented, and their discontent takes reactionary form, then socialists need to have more to say than “stop being so stupid.”
Eyes Left What to make of Lee Anderson’s political trajectory? | Morning Star
https://morningstaronline.co.uk/a…

What to make of Lee Anderson’s political trajectory?
While the Labour-turned-Tory-turned-Reform UK politician might hold deeply objectionable views, there are lessons to be drawn about class discontent and how socialist leadership should respond, argues ANDREW MURRAY

This https://arxiv.org/abs/2309.10924 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Change of Scenery: Unsupervised LiDAR Change Detection for Mobile Robots
This paper presents a fully unsupervised deep change detection approach for mobile robots with 3D LiDAR. In unstructured environments, it is infeasible to define a closed set of semantic classes. Instead, semantic segmentation is reformulated as binary change detection. We develop a neural network, RangeNetCD, that uses an existing point-cloud map and a live LiDAR scan to detect scene changes with respect to the map. Using a novel loss function, existing point-cloud semantic segmentation networ…

A time-stepping deep gradient flow method for option pricing in (rough) diffusion models
Antonis Papapantoleon, Jasper Rou
https://arxiv.org/abs/2403.00746

A time-stepping deep gradient flow method for option pricing in (rough) diffusion models
We develop a novel deep learning approach for pricing European options in diffusion models, that can efficiently handle high-dimensional problems resulting from Markovian approximations of rough volatility models. The option pricing partial differential equation is reformulated as an energy minimization problem, which is approximated in a time-stepping fashion by deep artificial neural networks. The proposed scheme respects the asymptotic behavior of option prices for large levels of moneyness,…

This https://arxiv.org/abs/2312.09353 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Residual U-net with Self-Attention to Solve Multi-Agent Time-Consistent Optimal Trade Execution
In this paper, we explore the use of a deep residual U-net with self-attention to solve the the continuous time time-consistent mean variance optimal trade execution problem for multiple agents and assets. Given a finite horizon we formulate the time-consistent mean-variance optimal trade execution problem following the Almgren-Chriss model as a Hamilton-Jacobi-Bellman (HJB) equation. The HJB formulation is known to have a viscosity solution to the unknown value function. We reformulate the HJB…