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08/22/2023
An extensible point-based method for data chart value detection
We present an extensible method for identifying semantic points to rever...
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07/17/2023
Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge
Understanding protein interactions and pathway knowledge is crucial for ...
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07/12/2023
SwiFT: Swin 4D fMRI Transformer
The modeling of spatiotemporal brain dynamics from high-dimensional data...
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06/07/2023
Optimal sensor placement for reconstructing wind pressure field around buildings using compressed sensing
Deciding how to optimally deploy sensors in a large, complex, and spatia...
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03/28/2023
Rethinking CycleGAN: Improving Quality of GANs for Unpaired Image-to-Image Translation
An unpaired image-to-image (I2I) translation technique seeks to find a m...
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02/16/2023
A Neural PDE Solver with Temporal Stencil Modeling
Numerical simulation of non-linear partial differential equations plays ...
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01/03/2023
Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response
There are various sources of ionizing radiation exposure, where medical ...
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03/04/2022
UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translation
Image-to-image translation has broad applications in art, design, and sc...
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02/23/2022
A Bayesian Deep Learning Approach to Near-Term Climate Prediction
Since model bias and associated initialization shock are serious shortco...
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01/25/2022
A Machine Learning-based Characterization Framework for Parametric Representation of Nonlinear Sloshing
The growing interest in creating a parametric representation of liquid s...
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11/09/2021
Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder
Real-time data collection and analysis in large experimental facilities ...
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08/27/2021
Feature Importance in a Deep Learning Climate Emulator
We present a study using a class of post-hoc local explanation methods i...
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06/24/2021
Stochastic Projective Splitting: Solving Saddle-Point Problems with Multiple Regularizers
We present a new, stochastic variant of the projective splitting (PS) fa...
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03/22/2021
Federated Quantum Machine Learning
Distributed training across several quantum computers could significantl...
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03/10/2021
Quantum machine learning with differential privacy
Quantum machine learning (QML) can complement the growing trend of using...
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01/15/2021
Hybrid Quantum-Classical Graph Convolutional Network
The high energy physics (HEP) community has a long history of dealing wi...
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12/22/2020
Quantum Convolutional Neural Networks for High Energy Physics Data Analysis
This work presents a quantum convolutional neural network (QCNN) for the...
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09/03/2020
Quantum Long Short-Term Memory
Long short-term memory (LSTM) is a kind of recurrent neural networks (RN...
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08/31/2020
Chimbuko: A Workflow-Level Scalable Performance Trace Analysis Tool
Because of the limits input/output systems currently impose on high-perf...
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02/20/2020
Bounding the expected run-time of nonconvex optimization with early stopping
This work examines the convergence of stochastic gradient-based optimiza...
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06/13/2019
Layered SGD: A Decentralized and Synchronous SGD Algorithm for Scalable Deep Neural Network Training
Stochastic Gradient Descent (SGD) is the most popular algorithm for trai...
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05/21/2019
Performance Analysis of Deep Learning Workloads on Leading-edge Systems
This work examines the performance of leading-edge systems designed for ...
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03/05/2019
Change Detection with the Kernel Cumulative Sum Algorithm
Online change detection involves monitoring a stream of data for changes...
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02/04/2019