Univariate interpolation by exponential functions and Gaussian RBFs for generic sets of nodes. - Dmitry Yarotsky (J. Approx. Theory, 2013)

Examples of inconsistency in optimization by expected improvement. - Dmitry Yarotsky (J. Glob. Optim., 2013)

GTApprox: Surrogate modeling for industrial design. - Mikhail Belyaev; Evgeny Burnaev; Ermek Kapushev; Maxim Panov; Pavel V. Prikhodko; Dmitry P. Vetrov; Dmitry Yarotsky (Adv. Eng. Softw., 2016)

Railway Incident Ranking with Machine Learning. - Evgeni Bikov; Pavel Boyko; Evgeny Sokolov; Dmitry Yarotsky (ICMLA, 2017)

Geometric features for voxel-based surface recognition. - Dmitry Yarotsky (CoRR, 2017)

Quantified advantage of discontinuous weight selection in approximations with deep neural networks. - Dmitry Yarotsky (CoRR, 2017)

Error bounds for approximations with deep ReLU networks. - Dmitry Yarotsky (Neural Networks, 2017)

Optimal approximation of continuous functions by very deep ReLU networks. - Dmitry Yarotsky (COLT, 2018)

Unused Beam Reservation for PAPR Reduction in Massive MIMO System. - Andrey Ivanov 001; Artyom Volokhatyi; Dmitry Lakontsev; Dmitry Yarotsky (VTC Spring, 2018)

Smart Sorting in Massive MIMO Detection. - Andrey Ivanov 001; Dmitry Yarotsky; Maria Stoliarenko; Alexey A. Frolov (WiMob, 2018)

Universal approximations of invariant maps by neural networks. - Dmitry Yarotsky (CoRR, 2018)

Collective evolution of weights in wide neural networks. - Dmitry Yarotsky (CoRR, 2018)

Iterative Nonlinear Detection and Decoding in Multi-User Massive MIMO. - Andrey Ivanov 001; Andrey Savinov; Dmitry Yarotsky (IWCMC, 2019)

Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO. - Alexander Osinsky; Andrey Ivanov 001; Dmitry Yarotsky (ICASSP, 2020)

Low-loss connection of weight vectors: distribution-based approaches. - Ivan Anokhin; Dmitry Yarotsky (ICML, 2020)

The phase diagram of approximation rates for deep neural networks. - Dmitry Yarotsky; Anton Zhevnerchuk (NeurIPS, 2020)

High Performance Interference Suppression in Multi-User Massive MIMO Detector. - Andrey Ivanov 001; Alexander Osinsky; Dmitry Lakontsev; Dmitry Yarotsky (VTC Spring, 2020)

Data-Aided LS Channel Estimation in Massive MIMO Turbo-Receiver. - Alexander Osinsky; Andrey Ivanov 001; Dmitry Lakontsev; Roman Bychkov; Dmitry Yarotsky (VTC Spring, 2020)

Bayesian Approach to Channel Interpolation in Massive MIMO Receiver. - Alexander Osinsky; Andrey Ivanov 001; Dmitry Yarotsky (IEEE Commun. Lett., 2020)

Elementary superexpressive activations. - Dmitry Yarotsky (ICML, 2021)

Explicit loss asymptotics in the gradient descent training of neural networks. - Maksim Velikanov; Dmitry Yarotsky (NeurIPS, 2021)

Data-Driven Beams Selection for Beamspace Channel Estimation in Massive MIMO. - Roman Bychkov; Alexander Osinsky; Andrey Ivanov 001; Dmitry Yarotsky (VTC Spring, 2021)

Spatial Denoising for Sparse Channel Estimation in Coherent Massive MIMO. - Alexander Osinsky; Andrey Ivanov 001; Dmitry Yarotsky (VTC Fall, 2021)

Adaptive Channel Interpolation in High-Speed Massive MIMO. - Alexander Osinsky; Roman Bychkov; Andrey Ivanov 001; Dmitry Yarotsky (VTC Spring, 2021)

Machine Learning-Assisted Channel Estimation in Massive MIMO Receiver. - Dmitry Yarotsky; Andrey Ivanov 001; Roman Bychkov; Alexander Osinsky; Andrey Savinov; Mikhail Trefilov; Vladimir Lyashev 001 (VTC Spring, 2021)

Universal scaling laws in the gradient descent training of neural networks. - Maksim Velikanov; Dmitry Yarotsky (CoRR, 2021)

Efficient Performance Bound for Channel Estimation in Massive MIMO Receiver. - Alexander Osinsky; Andrey Ivanov 001; Dmitry Yarotsky (IEEE Trans. Wirel. Commun., 2021)

Machine Learning-Assisted PAPR Reduction in Massive MIMO. - Aleksei Kalinov; Roman Bychkov; Andrey Ivanov 001; Alexander Osinsky; Dmitry Yarotsky (IEEE Wirel. Commun. Lett., 2021)

Lower Performance Bound for Beamspace Channel Estimation in Massive MIMO. - Alexander Osinsky; Andrey Ivanov 001; Dmitry Lakontsev; Dmitry Yarotsky (IEEE Wirel. Commun. Lett., 2021)

Embedded Ensembles: infinite width limit and operating regimes. - Maksim Velikanov; Roman V. Kail; Ivan Anokhin; Roman Vashurin; Maxim Panov; Alexey Zaytsev 002; Dmitry Yarotsky (AISTATS, 2022)

A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta. - Maksim Velikanov; Denis Kuznedelev; Dmitry Yarotsky (ICLR, 2023)

Structure of universal formulas. - Dmitry Yarotsky (NeurIPS, 2023)

Beamspace Selection in Multi-User Massive MIMO. - Vladislav Molodtsov; Roman Bychkov; Alexander Osinsky; Dmitry Yarotsky; Andrey Ivanov 001 (IEEE Access, 2023)

Training FFT to Select Beams in Massive MIMO. - Vladislav Molodtsov; Roman Bychkov; Alexander Osinsky; Andrey Ivanov 001; Dmitry Yarotsky (IEEE Wirel. Commun. Lett., 2023)

Generalization error of spectral algorithms. - Maksim Velikanov; Maxim Panov; Dmitry Yarotsky (ICLR, 2024)

Learnability of high-dimensional targets by two-parameter models and gradient flow. - Dmitry Yarotsky (NeurIPS, 2024)

Learning high-dimensional targets by two-parameter models and gradient flow. - Dmitry Yarotsky (CoRR, 2024)

Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions. - Maksim Velikanov; Dmitry Yarotsky (J. Mach. Learn. Res., 2024)

SGD with memory: fundamental properties and stochastic acceleration. - Dmitry Yarotsky; Maksim Velikanov (ICLR, 2025)

Corner Gradient Descent. - Dmitry Yarotsky (CoRR, 2025)