Zobrazeno 1 - 10
of 9 281
pro vyhledávání: '"A, Pesenti"'
We study optimal payoff choice for an expected utility maximizer under the constraint that their payoff is not allowed to deviate ``too much'' from a given benchmark. We solve this problem when the deviation is assessed via a Bregman-Wasserstein (BW)
Externí odkaz:
http://arxiv.org/abs/2411.18397
We present a computational explainability approach for human comparison tasks, using Alignment Importance Score (AIS) heatmaps derived from deep-vision models. The AIS reflects a feature-map's unique contribution to the alignment between Deep Neural
Externí odkaz:
http://arxiv.org/abs/2409.16292
Autor:
Miao, Kathleen E., Pesenti, Silvana M.
Elicitable functionals and (strict) consistent scoring functions are of interest due to their utility of determining (uniquely) optimal forecasts, and thus the ability to effectively backtest predictions. However, in practice, assuming that a distrib
Externí odkaz:
http://arxiv.org/abs/2409.04412
We consider the problem where an agent aims to combine the views and insights of different experts' models. Specifically, each expert proposes a diffusion process over a finite time horizon. The agent then combines the experts' models by minimising t
Externí odkaz:
http://arxiv.org/abs/2407.04860
Autor:
Jones, Chris, Pesenti, Lucas
We study a general class of nonlinear iterative algorithms which includes power iteration, belief propagation and approximate message passing, and many forms of gradient descent. When the input is a random matrix with i.i.d. entries, we use Boolean F
Externí odkaz:
http://arxiv.org/abs/2404.07881
Autor:
Pesenti, Silvana M., Vanduffel, Steven
We employ scoring functions, used in statistics for eliciting risk functionals, as cost functions in the Monge-Kantorovich (MK) optimal transport problem. This gives raise to a rich variety of novel asymmetric MK divergences, which subsume the family
Externí odkaz:
http://arxiv.org/abs/2311.12183
Differential sensitivity measures provide valuable tools for interpreting complex computational models used in applications ranging from simulation to algorithmic prediction. Taking the derivative of the model output in direction of a model parameter
Externí odkaz:
http://arxiv.org/abs/2310.06151
Autor:
Gaetano Florio, Eleonora Carlesso, Francesco Mojoli, Fabiana Madotto, Luigi Vivona, Chiara Minaudo, Michele Battistin, Sebastiano Maria Colombo, Stefano Gatti, Simone Sosio, Antonio Pesenti, Giacomo Grasselli, Alberto Zanella
Publikováno v:
BMC Anesthesiology, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Transpulmonary pressure is the effective pressure across the lung parenchyma and has been proposed as a guide for mechanical ventilation. The pleural pressure is challenging to directly measure in clinical setting and esophageal m
Externí odkaz:
https://doaj.org/article/ff69d10334b9404fa789b2cad9405124
Autor:
Daniele Vinciguerra, Rajalakshmi P S, Jane Yang, Panagiotis G. Georgiou, Katherine Snell, Théo Pesenti, Jeffrey Collins, Mikayla Tamboline, Shili Xu, R. Michael van Dam, Kathryn M. M. Messina, Andrea L. Hevener, Heather D. Maynard
Publikováno v:
ACS Central Science, Vol 10, Iss 11, Pp 2036-2047 (2024)
Externí odkaz:
https://doaj.org/article/0c54b06039ce4440b2130fcca3f81581
Autor:
Wei Ming Lim, Wei-Xiang Chew, Arianna Esposito Verza, Marion Pesenti, Andrea Musacchio, Thomas Surrey
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract During cell division, the microtubule cytoskeleton undergoes dramatic cell cycle-driven reorganizations of its architecture. Coordinated by changes in the phosphorylation patterns of a multitude of microtubule associated proteins, the mitoti
Externí odkaz:
https://doaj.org/article/d454476d561b476ebdc59947e9765265