On the Use of Shape-Constrained Splines for Biokinetic Process Modelling

About
Privacy
Disclaimer

Graph Chatbot

Related publications (30)

Spatially adaptive machine learning models for predicting water quality in Hong Kong

Water quality prediction in the spatially heterogeneous environment is challenging as the importance of water quality parameters (WQPs) and the performance of prediction models may vary across space. Thus, this study proposed spatially adaptive machine lea ...

ELSEVIER2023

A Comprehensive Timing Model for Accurate Frequency Tuning in Dataflow Circuits

Paolo Ienne, Andrea Guerrieri, Lana Josipovic, Carmine Rizzi

The ability of dataflow circuits to implement dynamic scheduling promises to overcome the conservatism of static scheduling techniques that high-level synthesis tools typically rely on. Yet, the same distributed control mechanism that allows dataflow circu ...

IEEE COMPUTER SOC2022

Poster World. Bespoke AI Meets Curator Expertise for Public Engagement

Mathieu Salzmann, Delphine Ribes Lemay, Nicolas Henchoz, Emily Clare Groves, Andrea Regula Schneider

Though museums are digitising their archives, online consultations remain low. New forms of engagement bring these digital memories to life and can support museums in maintaining and developing digital resources. Artificial Intelligence presents opportunit ...

2022

Lippmann Photography: A Signal Processing Perspective

Martin Vetterli, Arnaud Latty, Adam James Scholefield, Gilles Baechler, Michalina Wanda Pacholska

Lippmann (or interferential) photography is the first and only analog photography method that can capture the full color spectrum of a scene in a single take. This technique, invented more than a hundred years ago, records the colors by creating interferen ...

2022

Taming neuronal noise with large networks

Valentin Marc Schmutz

How does reliable computation emerge from networks of noisy neurons? While individual neurons are intrinsically noisy, the collective dynamics of populations of neurons taken as a whole can be almost deterministic, supporting the hypothesis that, in the br ...

EPFL2022

Lactate supply overtakes glucose when neural computational and cognitive loads scale up

Pierre Magistretti

Neural computational power is determined by neuroenergetics, but how and which energy substrates are allocated to various forms of memory engram is unclear. To solve this question, we asked whether neuronal fueling by glucose or lactate scales differently ...

National Academy of Sciences2022

Development of a reduced model for energetic particle transport by sawteeth in tokamaks

Mario Ludovico Podesta, Francesca Maria Poli, Anna Teplukhina, Matteo Vallar, Jiangyan Yang

The sawtooth instability is known for inducing transport and loss of energetic particles (EPs), and for generating seed magnetic islands that can trigger tearing modes. Both effects degrade the overall plasma performance. Several theories and numerical mod ...

2022

Are socially-aware trajectory prediction models really socially-aware?

Alexandre Massoud Alahi, Seyed Mohsen Moosavi Dezfooli, Saeed Saadatnejad, Mohammadhossein Bahari, Pedram Khorsandi

Our transportation field has recently witnessed an arms race of neural network-based trajectory predictors. While these predictors are at the core of many applications such as autonomous navigation or pedestrian flow simulations, their adversarial robustne ...

2022

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

Matthieu Wyart, Umberto Maria Tomasini, Antonio Sclocchi

Recently, several theories including the replica method made predictions for the generalization error of Kernel Ridge Regression. In some regimes, they predict that the method has a 'spectral bias': decomposing the true function f* on the eigenbasis of the ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Data integration for the numerical simulation of cardiac electrophysiology

Alfio Quarteroni, Andrea Manzoni, Luca Dede', Stefano Pagani

The increasing availability of extensive and accurate clinical data is rapidly shaping cardiovascular care by improving the understanding of physiological and pathological mechanisms of the cardiovascular system and opening new frontiers in designing thera ...

WILEY2021

Page 3 of 3

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

Matthieu Wyart, Umberto Maria Tomasini, Antonio Sclocchi

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022