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Found 6 papers, 0 papers with code
Deeper Hedging: A New Agent-based Model for Effective Deep Hedging
With the proposed Chiarella-Heston model, we generate a training dataset to train a deep hedging agent for optimal hedging strategies under various transaction cost levels.
AI enhanced finite element multiscale modelling and structural uncertainty analysis of a functionally graded porous beam
The error range of CNN models leads to an uncertain mechanical performance, which is further evaluated in a structural uncertainty analysis on the FG porous three-layer beam consisting of two thin high-density layers and a thick low-density one, where the imprecise CNN predicted moduli are represented as triangular fuzzy numbers in double parametric form.
Understanding intra-day price formation process by agent-based financial market simulation: calibrating the extended chiarella model
It is shown that the machine learning surrogate learned in the proposed method is an accurate proxy of the true agent-based market simulation.
High-frequency financial market simulation and flash crash scenarios analysis: an agent-based modelling approach
We scrutinise the market dynamics during the simulated flash crash and show that the simulated dynamics are consistent with what happened in historical flash crash scenarios.
Training-Based Equivalence Relations in Large-Scale Quantized Communication Systems
We show that a quantized large-scale system with unknown parameters and training signals can be analyzed by examining an equivalent system with known parameters by modifying the signal power and noise variance in a prescribed manner.
Quantization
Information Theory
Information Theory
Analyzing Training Using Phase Transitions in Entropy---Part I: General Theory
We analyze phase transitions in the conditional entropy of a sequence caused by a change in the conditional variables or input distribution.
One-Shot Learning
Information Theory
Information Theory
