Zobrazeno 1 - 10
of 2 401
pro vyhledávání: '"Pesenti, P."'
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 first-order iterative algorithms which includes power iteration, belief propagation and Approximate Message Passing (AMP), and many forms of gradient descent. When the input is a random matrix with i.i.d. entries, we prese
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
We give new rounding schemes for SDP relaxations for the problems of maximizing cubic polynomials over the unit sphere and the $n$-dimensional hypercube. In both cases, the resulting algorithms yield a $O(\sqrt{n/k})$ multiplicative approximation in
Externí odkaz:
http://arxiv.org/abs/2310.00393
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
Autor:
Emanuele Rezoagli, Carla Fornari, Roberto Fumagalli, Giacomo Grasselli, Carlo Alberto Volta, Paolo Navalesi, Rihard Knafelj, Laurent Brochard, Antonio Pesenti, Tommaso Mauri, Giuseppe Foti, for the Pleural Pressure Working Group (PLUG)
Publikováno v:
Annals of Intensive Care, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Background Sigh breaths may impact outcomes in acute hypoxemic respiratory failure (AHRF) during assisted mechanical ventilation. We investigated whether sigh breaths may impact mortality in predefined subgroups of patients enrolled in the P
Externí odkaz:
https://doaj.org/article/8589f37855c74c03ada16eb095d1240f
We introduce a framework for quantifying propagation of uncertainty arising in a dynamic setting. Specifically, we define dynamic uncertainty sets designed explicitly for discrete stochastic processes over a finite time horizon. These dynamic uncerta
Externí odkaz:
http://arxiv.org/abs/2308.12856