activity
20172020
most citedCombining Static and Dynamic Features for Multivariate Sequence Classification

39 citations · 47 across the 2 of their papers we have counts for

collaborators

5 papers

q-bio.NC2020

Understanding Information Processing in Human Brain by Interpreting Machine Learning Models

Ilya Kuzovkin

The thesis explores the role machine learning methods play in creating intuitive computational models of neural processing. Combined with interpretability techniques, machine learn…

cs.LG2019

OffWorld Gym: open-access physical robotics environment for real-world reinforcement learning benchmark and research

Ashish Kumar, Toby Buckley, John B. Lanier +3

Success stories of applied machine learning can be traced back to the datasets and environments that were put forward as challenges for the community. The challenge that the commun…

eess.SP20198 cited

Direct information transfer rate optimisation for SSVEP-based BCI

Anti Ingel, Ilya Kuzovkin, Raul Vicente

In this work, a classification method for SSVEP-based BCI is proposed. The classification method uses features extracted by traditional SSVEP-based BCI methods and finds optimal di…

cs.AI2019

Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs

Himanshu Sahni, Toby Buckley, Pieter Abbeel +1

Reinforcement Learning (RL) algorithms typically require millions of environment interactions to learn successful policies in sparse reward settings. Hindsight Experience Replay (H…

cs.LG201739 cited

Combining Static and Dynamic Features for Multivariate Sequence Classification

Anna Leontjeva, Ilya Kuzovkin

Model precision in a classification task is highly dependent on the feature space that is used to train the model. Moreover, whether the features are sequential or static will dict…