4 citations · 7 across the 5 of their papers we have counts for
5 papers
DSS: Synthesizing long Digital Ink using Data augmentation, Style encoding and Split generation
Aleksandr Timofeev, Anastasiia Fadeeva, Andrei Afonin +2
As text generative models can give increasingly long answers, we tackle the problem of synthesizing long text in digital ink. We show that the commonly used models for this task fa…
Sampling and Ranking for Digital Ink Generation on a tight computational budget
Andrei Afonin, Andrii Maksai, Aleksandr Timofeev +1
Digital ink (online handwriting) generation has a number of potential applications for creating user-visible content, such as handwriting autocompletion, spelling correction, and b…
Can we learn gradients by Hamiltonian Neural Networks?
Aleksandr Timofeev, Andrei Afonin, Yehao Liu
In this work, we propose a meta-learner based on ODE neural networks that learns gradients. This approach makes the optimizer is more flexible inducing an automatic inductive bias…
Towards Model Agnostic Federated Learning Using Knowledge Distillation
Andrei Afonin, Sai Praneeth Karimireddy
Is it possible to design an universal API for federated learning using which an ad-hoc group of data-holders (agents) collaborate with each other and perform federated learning? Su…
Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation and Optimal Measurement Placement in Power Systems?
Andrei Afonin, Michael Chertkov
We consider a power transmission system monitored with Phasor Measurement Units (PMUs) placed at significant, but not all, nodes of the system. Assuming that a sufficient number of…