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pro vyhledávání: '"Gauthier P."'
Computational modeling is an integral part of catalysis research. With it, new methodologies are being developed and implemented to improve the accuracy of simulations while reducing the computational cost. In particular, specific machine-learning te
Externí odkaz:
http://arxiv.org/abs/2408.14577
Autor:
Góis, António, Mofakhami, Mehrnaz, Santos, Fernando P., Lacoste-Julien, Simon, Gidel, Gauthier
Predictions often influence the reality which they aim to predict, an effect known as performativity. Existing work focuses on accuracy maximization under this effect, but model deployment may have important unintended impacts, especially in multiage
Externí odkaz:
http://arxiv.org/abs/2408.05146
Autor:
Simjanovski, Simeon, Gauthier, Guillaume, Rubinsztein-Dunlop, Halina, Reeves, Matthew T., Neely, Tyler W.
We study the creation and breakdown of a quantized vortex shear layer forming between a stationary Bose-Einstein condensate and a stirred-in persistent current. Once turbulence is established, we characterize the progressive clustering of the vortice
Externí odkaz:
http://arxiv.org/abs/2408.02200
Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of each feature's value to the prediction. This requires a scalar prediction as in binary classification,
Externí odkaz:
http://arxiv.org/abs/2408.01382
We present a dynamic hedging scheme for S&P 500 options, where rebalancing decisions are enhanced by integrating information about the implied volatility surface dynamics. The optimal hedging strategy is obtained through a deep policy gradient-type r
Externí odkaz:
http://arxiv.org/abs/2407.21138
The recent work of Horikawa and Nakagawa (2024) claims that under a complete market admitting statistical arbitrage, the difference between the hedging position provided by deep hedging and that of the replicating portfolio is a statistical arbitrage
Externí odkaz:
http://arxiv.org/abs/2407.14736
Thanks to their parallel and sparse activity features, recurrent neural networks (RNNs) are well-suited for hardware implementation in low-power neuromorphic hardware. However, mapping rate-based RNNs to hardware-compatible spiking neural networks (S
Externí odkaz:
http://arxiv.org/abs/2407.13534
Autor:
Gauthier, Thomas
In this note we study common preperiodic points of rational maps of the Riemann Sphere. We show that given any degrees $d_1,d_2\geq2$, outside a Zariski closed subset of the space of pairs of rational maps $(f,g)$ of degree $d_1$ and $d_2$ respective
Externí odkaz:
http://arxiv.org/abs/2407.13275
We study the production of three electroweak gauge bosons at the LHC, in the effective field theory of the standard model, at dimension six and next-to-leading order in QCD. We present results for inclusive cross-sections and differential distributio
Externí odkaz:
http://arxiv.org/abs/2407.09600
This article seeks to contribute to a nuanced understanding of the integration of Design Structure Matrix (DSM) and genetic algorithms in the context of Complex Systems modelling described within Model-Based System Engineering approach. By examining
Externí odkaz:
http://arxiv.org/abs/2407.03739