Publications related to Fast Circle Detection Using Gradient Pair Vectors

A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces

In this paper, we propose a reduced-order modeling strategy for two-way Dirichlet-Neumann parametric coupled problems solved with domain-decomposition (DD) sub-structuring methods. We split the original coupled differential problem into two sub-problems wi ...

New York2024

Efficient Continual Finite-Sum Minimization

Volkan Cevher, Efstratios Panteleimon Skoulakis, Leello Tadesse Dadi

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

2024

SIMPLE HIERARCHICAL PLANNING WITH DIFFUSION

Caglar Gulcehre, Chang Chen

Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in generalization, especially in capturing temporal abstractions for long- horizon tas ...

2024

Micropreparative Gel Electrophoresis for Purification of Nanoscale Bioconjugates

Ardemis Anoush Boghossian, Yahya Rabbani, Shang-Jung Wu, Vitalijs Zubkovs, Sayyed Hashem Sajjadi

Conventional techniques for purifying macromolecular conjugates often require complex and costly installments that are inaccessible to most laboratories. In this work, we develop a one-step micropreparative method based on a trilayered polyacrylamide gel e ...

2024

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Olga Fink, Ismail Nejjar, Mengjie Zhao

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these ...

2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Residual-based attention in physics-informed neural networks

Nikolaos Stergiopoulos, Sokratis Anagnostopoulos

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Lausanne2024

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Roya Moghaddasi Fereidani

Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

EPFL2024

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Evann Pierre Guy Courdier

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power.Simultaneously, a critical pain point arises as several computer vision applications are deployed ...

EPFL2024

Euclid: Improving the efficiency of weak lensing shear bias calibration

Frédéric Courbin, Georges Meylan, Malte Tewes, Yi Wang, Richard Massey, Marcello Farina

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and ...

Edp Sciences S A2024

Fast Circle Detection Using Gradient Pair Vectors

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A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces

Efficient Continual Finite-Sum Minimization

SIMPLE HIERARCHICAL PLANNING WITH DIFFUSION

Micropreparative Gel Electrophoresis for Purification of Nanoscale Bioconjugates

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Residual-based attention in physics-informed neural networks

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Euclid: Improving the efficiency of weak lensing shear bias calibration

A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces

SIMPLE HIERARCHICAL PLANNING WITH DIFFUSION

Micropreparative Gel Electrophoresis for Purification of Nanoscale Bioconjugates

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Residual-based attention in physics-informed neural networks

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Efficient Continual Finite-Sum Minimization

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Euclid: Improving the efficiency of weak lensing shear bias calibration