Dmitriy Pyrkin

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All published works

Action	Title	Year	Authors
+	Editable Neural Networks	2020	Anton Sinitsin Vsevolod Plokhotnyuk Dmitriy Pyrkin С. Б. Попов Artem Babenko
+	Editable Neural Networks	2020	Anton Sinitsin Vsevolod Plokhotnyuk Dmitriy Pyrkin Sergei Popov Artem Babenko

Common Coauthors

Coauthor	Papers Together
Artem Babenko	2
Anton Sinitsin	2
Vsevolod Plokhotnyuk	2
Sergei Popov	1
С. Б. Попов	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Distilling the Knowledge in a Neural Network	2015	Geoffrey E. Hinton Oriol Vinyals Jay B. Dean	1
+ PDF Chat	Rethinking the Inception Architecture for Computer Vision	2016	Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jon Shlens Zbigniew Wojna	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	Overcoming catastrophic forgetting in neural networks	2017	James Kirkpatrick Razvan Pascanu Neil C. Rabinowitz Joel Veness Guillaume Desjardins Andrei A. Rusu Kieran Milan John Quan Tiago Ramalho Agnieszka Grabska‐Barwińska	1
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	1
+	Evolved Policy Gradients	2018	Rein Houthooft Richard Y. Chen Phillip Isola Bradly C. Stadie Filip Wolski Jonathan Ho Pieter Abbeel	1
+	HotFlip: White-Box Adversarial Examples for Text Classification	2018	Javid Ebrahimi Anyi Rao Daniel Lowd Dejing Dou	1
+	fairseq: A Fast, Extensible Toolkit for Sequence Modeling.	2019	Myle Ott Sergey Edunov Alexei Baevski Angela Fan Sam Gross Nathan Ng David Grangier Michael Auli	1
+	Adversarial Examples: Attacks and Defenses for Deep Learning	2019	Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li	1
+	Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)	2015	Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter	1
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	1
+ PDF Chat	Densely Connected Convolutional Networks	2017	Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger	1
+ PDF Chat	Super-convergence: very fast training of neural networks using large learning rates	2019	Leslie N. Smith Nicholay Topin	1
+	signSGD: Compressed Optimisation for Non-Convex Problems	2018	Jeremy Bernstein Yu-Xiang Wang Kamyar Azizzadenesheli Animashree Anandkumar	1
+	Learning to learn by gradient descent by gradient descent	2016	Marcin Andrychowicz Misha Denil Sergio Luis Suárez Gómez Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas	1
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	1
+	Universal Adversarial Triggers for Attacking and Analyzing NLP	2019	Eric Wallace Shi Feng Nikhil Kandpal Matt Gardner Sameer Singh	1
+	ADADELTA: An Adaptive Learning Rate Method	2012	Matthew D. Zeiler	1