
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs
We consider a meshbased approach for training a neural network to produ...
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Differentiable Spline Approximations
The paradigm of differentiable programming has significantly enhanced th...
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NURBSDiff: A Differentiable NURBS Layer for Machine Learning CAD Applications
Recent deeplearningbased techniques for the reconstruction of geometri...
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Distributed Multigrid Neural Solvers on Megavoxel Domains
We consider the distributed training of largescale neural networks that...
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CrossGradient Aggregation for Decentralized Learning from NonIID data
Decentralized learning enables a group of collaborative agents to learn ...
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Physicsconsistent deep learning for structural topology optimization
Topology optimization has emerged as a popular approach to refine a comp...
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Decentralized Deep Learning using MomentumAccelerated Consensus
We consider the problem of decentralized deep learning where multiple ag...
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A SaddlePoint Dynamical System Approach for Robust Deep Learning
We propose a novel discretetime dynamical systembased framework for ac...
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On Higherorder Moments in Adam
In this paper, we investigate the popular deep learning optimization rou...
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Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning
Microfluidic devices are utilized to control and direct flow behavior in...
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3D Deep Learning with voxelized atomic configurations for modeling atomistic potentials in complex solidsolution alloys
The need for advanced materials has led to the development of complex, m...
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MultiResolution 3D Convolutional Neural Networks for Object Recognition
Learning from 3D Data is a fascinating idea which is well explored and s...
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On ConsensusOptimality Tradeoffs in Collaborative Deep Learning
In distributed machine learning, where agents collaboratively learn from...
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A ForwardBackward Approach for Visualizing Information Flow in Deep Networks
We introduce a new, systematic framework for visualizing information flo...
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Learning and Visualizing Localized Geometric Features Using 3DCNN: An Application to Manufacturability Analysis of Drilled Holes
3D Convolutional Neural Networks (3DCNN) have been used for object reco...
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Collaborative Deep Learning in Fixed Topology Networks
There is significant recent interest to parallelize deep learning algori...
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A MachineLearning Framework for Design for Manufacturability
this is a duplicate submission(original is arXiv:1612.02141). Hence want...
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Learning Localized Geometric Features Using 3DCNN: An Application to Manufacturability Analysis of Drilled Holes
3D convolutional neural networks (3DCNN) have been used for object reco...
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Aditya Balu
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