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09/12/2023
MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling
We propose MatSci ML, a novel benchmark for modeling MATerials SCIence u...
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10/31/2022
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science
We present the Open MatSci ML Toolkit: a flexible, self-contained, and s...
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03/29/2022
Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Design
Being able to predict the performance of circuits without running expens...
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12/18/2021
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs
Structured video representation in the form of dynamic scene graphs is a...
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10/14/2021
Connection Management xAPP for O-RAN RIC: A Graph Neural Network and Reinforcement Learning Approach
Connection management is an important problem for any wireless network t...
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06/06/2021
On Local Aggregation in Heterophilic Graphs
Many recent works have studied the performance of Graph Neural Networks ...
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04/06/2021
Structured Citation Trend Prediction Using Graph Neural Networks
Academic citation graphs represent citation relationships between public...
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03/02/2020
Permutohedral-GCN: Graph Convolutional Networks with Global Attention
Graph convolutional networks (GCNs) update a node's feature vector by ag...
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12/13/2018
Conditional Graph Neural Processes: A Functional Autoencoder Approach
We introduce a novel encoder-decoder architecture to embed functional pr...
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11/06/2017
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
Deep neural networks are commonly developed and trained in 32-bit floati...
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06/07/2013
A Factor Graph Approach to Joint OFDM Channel Estimation and Decoding in Impulsive Noise Environments
We propose a novel receiver for orthogonal frequency division multiplexi...
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03/05/2013
Impulsive Noise Mitigation in Powerline Communications Using Sparse Bayesian Learning
Additive asynchronous and cyclostationary impulsive noise limits communi...
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02/09/2012