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Open vocabulary models (e.g. CLIP) have shown strong performance on zero-shot classification through their ability generate embeddings for each class based on their (natural language) names. Prior work has focused on improving the accuracy…

Computer Vision and Pattern Recognition · Computer Science 2023-06-01 Zachary Novack , Julian McAuley , Zachary C. Lipton , Saurabh Garg

The Grist project (http://grist.caltech.edu/) is developing a grid-technology based system as a research environment for astronomy with massive and complex datasets. This knowledge extraction system will consist of a library of distributed…

Classical methods to model topological properties of point clouds, such as the Vietoris-Rips complex, suffer from the combinatorial explosion of complex sizes. We propose a novel technique to approximate a multi-scale filtration of the Rips…

Computational Geometry · Computer Science 2016-04-04 Aruni Choudhary , Michael Kerber , Sharath Raghvendra

With the approach of exascale computing era, particle-based models are becoming the focus of research due to their excellent scalability. We present a new code, Slurm, which implements the classic particle-in-cell algorithm for modeling…

Computational Physics · Physics 2018-12-05 Vyacheslav Olshevsky , Fabio Bacchini , Stefaan Poedts , Giovanni Lapenta

Cartesian-grid methods in combination with immersed-body and volume-of-fluid methods are ideally suited for simulating breaking waves around ships. A surface panelization of the ship hull is used as input to impose body-boundary conditions…

Fluid Dynamics · Physics 2014-10-10 Thomas T. O'Shea , Kyle A. Brucker , Douglas G. Dommermuth , Donald C. Wyatt

Machine learning (ML) techniques, in particular supervised regression algorithms, are a promising new way to use multiple observables to predict a cluster's mass or other key features. To investigate this approach we use the \textsc{MACSIS}…

Cosmology and Nongalactic Astrophysics · Physics 2019-01-16 Thomas J. Armitage , Scott T. Kay , David J. Barnes

When is good, good enough? This question lingers in approximation theory and numerical methods as a competition between accuracy and practicality. Numerical Analysis is traditionally where the rubber meets the road: students begin to use…

History and Overview · Mathematics 2019-02-21 Nicholas A. Battista , Matthew S. Mizuhara

Recent advances in visual-language models have shown remarkable zero-shot text-image matching ability that is transferable to downstream tasks such as object detection and segmentation. Adapting these models for object counting, however,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-11 Ruixiang Jiang , Lingbo Liu , Changwen Chen

This paper introduces the first, open source software library for Constraint Consistent Learning (CCL). It implements a family of data-driven methods that are capable of (i) learning state-independent and -dependent constraints, (ii)…

Robotics · Computer Science 2020-02-19 Yuchen Zhao , Jeevan Manavalan , Prabhakar Ray , Hsiu-Chin Lin , Matthew Howard

The accurate reconstruction of immiscible fluid-fluid interfaces from the volume fraction field is a critical component of geometric Volume of Fluid (VOF) methods. A common strategy is the Piecewise Linear Interface Calculation (PLIC),…

Computational Physics · Physics 2024-08-05 Andrew Cahaly , Fabien Evrard , Olivier Desjardins

The paper develops a method for the numerical simulation of a free-surface flow of incompressible viscous fluid around a streamlined body. The body is a rigid stationary construction partially submerged in the fluid. The application we are…

Incident management is essential to maintain the reliability and availability of cloud computing services. Cloud vendors typically disclose incident reports to the public, summarizing the failures and recovery process to help minimize their…

Performance · Computer Science 2026-03-18 Xiaoyu Chu , Shashikant Ilager , Yizhen Zang , Sacheendra Talluri , Alexandru Iosup

Nonlinear least squares data-fitting driven by physical process simulation is a classic and widely successful technique for the solution of inverse problems in science and engineering. Known as "Full Waveform Inversion" in application to…

Optimization and Control · Mathematics 2020-10-28 William W. Symes

Scientific machine learning (SciML) is an interdisciplinary research field that integrates machine learning, particularly deep learning, with physics theory to understand and predict complex natural phenomena. By incorporating physical…

Geophysics · Physics 2025-03-24 Tomohisa Okazaki

We present a new method of data clustering applied to earthquake catalogs, with the goal of reconstructing the seismically active part of fault networks. We first use an original method to separate clustered events from uncorrelated…

Geophysics · Physics 2015-05-19 Guy Ouillon , Didier Sornette

Hydrodynamic simulations have become irreplaceable in modern cosmology for exploring complex systems and making predictions to steer future observations. In Chapter 1, we begin with a philosophical discussion on the role of simulations in…

Cosmology and Nongalactic Astrophysics · Physics 2023-12-20 Edoardo Altamura

Reliable assessment of tropical cyclone (TC) risk is limited by the brevity and spatial sparsity of the historical record, particularly for the rare, high-intensity landfalls that dominate insured loss. We present WHITS (Wind-focused…

Machine Learning · Computer Science 2026-05-21 Jennifer Nakamura , Upmanu Lall

Numerous codes are being developed to solve Shallow Water equations. Because they are used in hydraulics and environmental studies, their capability to simulate properly flow dynamics is essential to guarantee infrastructure and human…

We propose a new tiling strategy, Flip-n-Slide, which has been developed for specific use with large Earth observation satellite images when the location of objects-of-interest (OoI) is unknown and spatial context can be necessary for class…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Ellianna Abrahams , Tasha Snow , Matthew R. Siegfried , Fernando Pérez

4D seismic inversion is the leading method to quantitatively monitor fluid flow dynamics in the subsurface, with applications ranging from enhanced oil recovery to subsurface CO2 storage. The process of inverting seismic data for reservoir…

Geophysics · Physics 2023-10-25 Juan Romero , Nick Luiken , Matteo Ravasi