Eugene A. Golikov

16 papers A* 3Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions. CoRR Dmitry Yarotsky, Eugene A. Golikov, Yaroslav Gusev
2025	J	`jnl`	A Generalization Bound for Nearly-Linear Networks. Trans. Mach. Learn. Res. Eugene A. Golikov
2024	J	`jnl`	A Generalization Bound for Nearly-Linear Networks. CoRR Eugene A. Golikov
2022	J	`jnl`	A review of neural architecture search. Neurocomputing Dilyara Baymurzina, Eugene A. Golikov, Mikhail Burtsev
2022	A*	`conf`	Feature Learning in $L_2$-regularized DNNs: Attraction/Repulsion and Sparsity. NeurIPS Arthur Jacot, Eugene A. Golikov, Clément Hongler, Franck Gabriel
2022	J	`jnl`	Feature Learning in L CoRR Arthur Jacot, Eugene A. Golikov, Clément Hongler, Franck Gabriel
2022	J	`jnl`	Neural Tangent Kernel: A Survey. CoRR Eugene A. Golikov, Eduard Pokonechny, Vladimir Korviakov
2022	A*	`conf`	Non-Gaussian Tensor Programs. NeurIPS Eugene A. Golikov, Greg Yang
2020	J	`jnl`	Dynamically Stable Infinite-Width Limits of Neural Classifiers. CoRR Eugene A. Golikov
2020	J	`jnl`	Notes on Deep Learning Theory. CoRR Eugene A. Golikov
2020	A*	`conf`	Towards a General Theory of Infinite-Width Limits of Neural Classifiers. ICML Eugene A. Golikov
2020	J	`jnl`	Towards a General Theory of Infinite-Width Limits of Neural Classifiers. CoRR Eugene A. Golikov
2019	J	`jnl`	An Essay on Optimization Mystery of Deep Learning. CoRR Eugene A. Golikov
2019	J	`jnl`	Quadratic number of nodes is sufficient to learn a dataset via gradient descent. CoRR Biswarup Das, Eugene A. Golikov
2018	J	`jnl`	Embedding-reparameterization procedure for manifold-valued latent variables in generative models. CoRR Eugene A. Golikov, Maksim Kretov
2017	J	`jnl`	Using stochastic computation graphs formalism for optimization of sequence-to-sequence model. CoRR Eugene A. Golikov, Vlad Zhukov, Maksim Kretov