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Port-Hamiltonian Approach to Neural Network Training

Port-Hamiltonian Approach to Neural Network Training

6 September 2019
Stefano Massaroli
Michael Poli
Federico Califano
Angela Faragasso
Jinkyoo Park
Atsushi Yamashita
Hajime Asama
ArXivPDFHTML

Papers citing "Port-Hamiltonian Approach to Neural Network Training"

14 / 14 papers shown
Title
Human-Robot Cooperative Distribution Coupling for Hamiltonian-Constrained Social Navigation
Human-Robot Cooperative Distribution Coupling for Hamiltonian-Constrained Social Navigation
Weizheng Wang
Chao Yu
Yu Wang
Byung-Cheol Min
380
2
0
20 Sep 2024
On the Variance of the Adaptive Learning Rate and Beyond
On the Variance of the Adaptive Learning Rate and Beyond
Liyuan Liu
Haoming Jiang
Pengcheng He
Weizhu Chen
Xiaodong Liu
Jianfeng Gao
Jiawei Han
ODL
284
1,905
0
08 Aug 2019
Hamiltonian Neural Networks
Hamiltonian Neural Networks
S. Greydanus
Misko Dzamba
J. Yosinski
PINN
AI4CE
118
894
0
04 Jun 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLM
SSL
SSeg
1.8K
94,891
0
11 Oct 2018
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock
Jeff Donahue
Karen Simonyan
262
5,394
0
28 Sep 2018
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
414
5,111
0
19 Jun 2018
Deep Neural Networks Motivated by Partial Differential Equations
Deep Neural Networks Motivated by Partial Differential Equations
Lars Ruthotto
E. Haber
AI4CE
124
490
0
12 Apr 2018
Visualizing the Loss Landscape of Neural Nets
Visualizing the Loss Landscape of Neural Nets
Hao Li
Zheng Xu
Gavin Taylor
Christoph Studer
Tom Goldstein
243
1,893
0
28 Dec 2017
The Expressive Power of Neural Networks: A View from the Width
The Expressive Power of Neural Networks: A View from the Width
Zhou Lu
Hongming Pu
Feicheng Wang
Zhiqiang Hu
Liwei Wang
99
894
0
08 Sep 2017
Deep Relaxation: partial differential equations for optimizing deep
  neural networks
Deep Relaxation: partial differential equations for optimizing deep neural networks
Pratik Chaudhari
Adam M. Oberman
Stanley Osher
Stefano Soatto
G. Carlier
135
154
0
17 Apr 2017
Mask R-CNN
Mask R-CNN
Kaiming He
Georgia Gkioxari
Piotr Dollár
Ross B. Girshick
ObjD
352
27,195
0
20 Mar 2017
The Power of Depth for Feedforward Neural Networks
The Power of Depth for Feedforward Neural Networks
Ronen Eldan
Ohad Shamir
216
732
0
12 Dec 2015
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,115
0
22 Dec 2014
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