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ORCIDEugene A. Golikov
Person information
- affiliation (PhD 2025): EPFL, Lausanne, Switzerland
- affiliation (former): Moscow Institute of Physics and Technology, Russia
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2020 – today
- 2026
[i11]Dmitry Yarotsky, Eugene A. Golikov, Yaroslav Gusev:
Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions. CoRR abs/2602.04548 (2026)- 2025
- [j2]Eugene A. Golikov:
A Generalization Bound for Nearly-Linear Networks. Trans. Mach. Learn. Res. 2025 (2025) - 2024
- [i10]Eugene A. Golikov:
A Generalization Bound for Nearly-Linear Networks. CoRR abs/2407.06765 (2024) - 2022
- [j1]Dilyara Baymurzina, Eugene A. Golikov, Mikhail Burtsev:
A review of neural architecture search. Neurocomputing 474: 82-93 (2022) - [c3]Eugene A. Golikov, Greg Yang:
Non-Gaussian Tensor Programs. NeurIPS 2022 - [c2]Arthur Jacot, Eugene A. Golikov, Clément Hongler, Franck Gabriel:
Feature Learning in $L_2$-regularized DNNs: Attraction/Repulsion and Sparsity. NeurIPS 2022 - [i9]Arthur Jacot, Eugene A. Golikov, Clément Hongler, Franck Gabriel:
Feature Learning in L2-regularized DNNs: Attraction/Repulsion and Sparsity. CoRR abs/2205.15809 (2022) - [i8]Eugene A. Golikov, Eduard Pokonechny, Vladimir Korviakov:
Neural Tangent Kernel: A Survey. CoRR abs/2208.13614 (2022) - 2020
- [c1]Eugene A. Golikov:
Towards a General Theory of Infinite-Width Limits of Neural Classifiers. ICML 2020: 3617-3626 - [i7]Eugene A. Golikov:
Towards a General Theory of Infinite-Width Limits of Neural Classifiers. CoRR abs/2003.05884 (2020) - [i6]Eugene A. Golikov:
Dynamically Stable Infinite-Width Limits of Neural Classifiers. CoRR abs/2006.06574 (2020) - [i5]Eugene A. Golikov:
Notes on Deep Learning Theory. CoRR abs/2012.05760 (2020)
2010 – 2019
- 2019
- [i4]Eugene A. Golikov:
An Essay on Optimization Mystery of Deep Learning. CoRR abs/1905.07187 (2019) - [i3]Biswarup Das, Eugene A. Golikov:
Quadratic number of nodes is sufficient to learn a dataset via gradient descent. CoRR abs/1911.05402 (2019) - 2018
- [i2]Eugene A. Golikov, Maksim Kretov:
Embedding-reparameterization procedure for manifold-valued latent variables in generative models. CoRR abs/1812.02769 (2018) - 2017
- [i1]Eugene A. Golikov, Vlad Zhukov, Maksim Kretov:
Using stochastic computation graphs formalism for optimization of sequence-to-sequence model. CoRR abs/1711.07724 (2017)
Coauthor Index
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