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Generalizing Outside the Training Set: When Can Neural Networks Learn
  Identity Effects?

Generalizing Outside the Training Set: When Can Neural Networks Learn Identity Effects?

9 May 2020
Simone Brugiapaglia
Maoqing Liu
P. Tupper
ArXiv (abs)PDFHTML

Papers citing "Generalizing Outside the Training Set: When Can Neural Networks Learn Identity Effects?"

5 / 5 papers shown
VC dimension of Graph Neural Networks with Pfaffian activation functions
VC dimension of Graph Neural Networks with Pfaffian activation functionsNeural Networks (NN), 2024
Giuseppe Alessio D’Inverno
Monica Bianchini
F. Scarselli
GNN
266
4
0
22 Jan 2024
On the approximation capability of GNNs in node
  classification/regression tasks
On the approximation capability of GNNs in node classification/regression tasks
Giuseppe Alessio D’Inverno
Monica Bianchini
M. Sampoli
F. Scarselli
535
17
0
16 Jun 2021
Interpreting intermediate convolutional layers of generative CNNs
  trained on waveforms
Interpreting intermediate convolutional layers of generative CNNs trained on waveformsIEEE/ACM Transactions on Audio Speech and Language Processing (TASLP), 2021
Gašper Beguš
Alan Zhou
372
8
0
19 Apr 2021
Invariance, encodings, and generalization: learning identity effects
  with neural networks
Invariance, encodings, and generalization: learning identity effects with neural networksNeural Computation (Neural Comput.), 2021
Simone Brugiapaglia
Matthew Liu
P. Tupper
OOD
240
6
0
21 Jan 2021
Identity-Based Patterns in Deep Convolutional Networks: Generative
  Adversarial Phonology and Reduplication
Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and ReduplicationTransactions of the Association for Computational Linguistics (TACL), 2020
Gašper Beguš
GANSSL
240
17
0
13 Sep 2020
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