Publications associées à Coupled Splines for Sparse Curve Fitting

Publications associées (19)

Micro- and nanofabrication techniques for single crystal diamond photonics

Synthetically grown high-quality single crystal diamond is an excellent base material for quantum photonics. Planar single crystal diamond substrates several square millimeters in size are nowadays commercially available. They can be precisely structured u ...

Elsevier2025

Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms

Michaël Unser, Alexis Marie Frederic Goujon, Sebastian Jonas Neumayer

We propose to learn non-convex regularizers with a prescribed upper bound on their weak-convexity modulus. Such regularizers give rise to variational denoisers that minimize a convex energy. They rely on few parameters (less than 15,000) and offer a signal ...

2024

A flexible framework for the design and optimization of water-excitation RF pulses using B-spline interpolation

Daniel Wenz

PurposeTo implement a flexible framework, named HydrOptiFrame, for the design and optimization of time-efficient water-excitation (WE) RF pulses using B-spline interpolation, and to characterize their lipid suppression performance. MethodsAn evolutionary o ...

WILEY2024

Development of performance portable spline solver for exa-scale plasma turbulence simulation

Emily Louise Bourne

This paper describes the development of performance portable spline building kernels on top of Kokkos-kernels. We wish to solve a single matrix equation with multiple right-hand sides. This problem is quite unique and thus neither Kokkos-kernels (direct me ...

Institute of Electrical and Electronics Engineers Inc.2024

From Master Equation to SPICE: A Platform to Model Cryo-CMOS Control for Qubits

Andrew James Wright Garcia, Edoardo Charbon, Vladimir Pesic

Cryogenic classical electronics for the control of qubits can be placed near quantum processors for a more compact system, ultimately enabling a highly scalable one. However, cryogenic operation poses very strict power requirements on electronics, in addit ...

IEEE2024

Self-Aware Social Learning Over Graphs

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Konstantinos Ntemos

In this paper we study the problem of social learning under multiple true hypotheses and self-interested agents that exchange information over a graph. In this setup, each agent receives data that might be generated from a different hypothesis (or state) t ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Dynamic personalized human body energy expenditure: Prediction using time series forecasting LSTM models

Dolaana Khovalyg, Arnab Chatterjee

Dynamic human energy expenditure (EE) consists of energy costs for resting metabolism, food digestion, physical activity, and thermoregulation. Currently, multiple models predict EE mainly concerning physical activity, thus, discarding other factors contri ...

ELSEVIER SCI LTD2023

Review: III-V infrared emitters on Si: fabrication concepts, device architectures and down-scaling with a focus on template-assisted selective epitaxy

Kirsten Emilie Moselund

The local integration of III-Vs on Si is relevant for a wide range of applications in electronics and photonics, since it combines a mature and established materials platform with desired physical properties such as a direct and tuneable bandgap and high m ...

IOP Publishing Ltd2023

Depth-optimal Buffer and Splitter Insertion and Optimization in AQFP Circuits

Giovanni De Micheli, Alessandro Tempia Calvino

The Adiabatic Quantum-Flux Parametron (AQFP) is an energy-efficient superconducting logic family. AQFP technology requires buffer and splitting elements (B/S) to be inserted to satisfy path-balancing and fanout-branching constraints. B/S insertion policies ...

IEEE2023

A novel fatigue life prediction methodology based on energy dissipation in viscoelastic materials (vol 152, 106457, 2021)

Thomas Keller, Ghazaleh Eslami

ELSEVIER SCI LTD2022

CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging

Jean-Philippe Thiran, Dimitris Perdios, Marcel Arditi, Florian Martinez, Manuel Vonlanthen

Ultrafast ultrasound (US) revolutionized biomedical imaging with its capability of acquiring full-view frames at over 1 kHz, unlocking breakthrough modalities such as shear-wave elastography and functional US neuroimaging. Yet, it suffers from strong diffr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

End-to-End Task-Oriented Dialog Modeling With Semi-Structured Knowledge Management

Antoine Bosselut, Silin Gao

Current task-oriented dialog (TOD) systems mostly manage structured knowledge (e.g. databases and tables) to guide the goal-oriented conversations. However, they fall short of handling dialogs which also involve unstructured knowledge (e.g. reviews and doc ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

An occupant-centric control framework for balancing comfort, energy use and hygiene in hot water systems: A model-free reinforcement learning approach

François Maréchal, Dolaana Khovalyg, Amirreza Heidari

Occupants' behavior is a major source of uncertainty for the optimal operation of building energy systems. The highly stochastic hot water use behavior of occupants has led to conservative operational strategies for hot water systems, that try to ensure oc ...

2022

Machine-learning for damage assessment of rubble stone masonry piers based on crack patterns

Radhakrishna Achanta, Amir Rezaie

Under seismic actions, stone masonry buildings are prone to damage. To assess the severity of damaged masonry buildings and their failure modes, engineers connect these problems to surface crack features, such as the crack width and the extent of cracking. ...

ELSEVIER2022

Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar, Christian Robert Abbet

Supervised learning is constrained by the availability of labeled data, which are especially expensive to acquire in the field of digital pathology. Making use of open-source data for pre-training or using domain adaptation can be a way to overcome this is ...

ELSEVIER2022

Development and Experimental Validation of Dissipative Embedded Column Base Connections for Enhanced Seismic Performance of Steel Moment-Resisting Frames

Dimitrios Lignos, Albano António De Abreu E Presa De Castro E Sousa, Hiroyuki Inamasu

This paper proposes a novel embedded column base (ECB) connection that defies the current paradigm in capacity-designed steel moment-resisting frames (MRFs) where column bases have been traditionally considered as nondissipative. In the proposed concept, a ...

2022

Interface modification to achieve high-efficiency and stable perovskite solar cells

Yuhang Liu, Linfeng Pan, Hongwei Zhu, Zhongjin Shen

The organic-inorganic hybrid perovskite solar cells (PSCs) achieve relatively high power conversion efficiencies (PCEs) over the past few years. However, defects on the surface and at the grain boundaries of the perovskite active layers are critical factor ...

ELSEVIER SCIENCE SA2022

Special Section Guest Editorial: Image and Video Compression Using Deep Neural Networks

Touradj Ebrahimi

IS&T & SPIE2021

Optimizing Adiabatic Quantum-Flux-Parametron (AQFP) Circuits using an Exact Database

Giovanni De Micheli, Dewmini Sudara Marakkalage

Adiabatic Quantum-Flux-Parametron (AQFP) is a family of superconducting electronic (SCE) circuits exhibiting high energy efficiency. In AQFP technology, logic gates require splitters to drive multiple fanouts and both the logic gates and the splitters are ...

IEEE2021