65 citations · 69 across the 3 of their papers we have counts for
5 papers
Imbedding Deep Neural Networks
Andrew Corbett, Dmitry Kangin
Continuous-depth neural networks, such as Neural ODEs, have refashioned the understanding of residual neural networks in terms of non-linear vector-valued optimal control problems.…
Skillful Precipitation Nowcasting using Deep Generative Models of Radar
Suman Ravuri, Karel Lenc, Matthew Willson +17
Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socio-economic needs of many sectors reliant on weather-de…
A review of radar-based nowcasting of precipitation and applicable machine learning techniques
Rachel Prudden, Samantha Adams, Dmitry Kangin +4
A 'nowcast' is a type of weather forecast which makes predictions in the very short term, typically less than two hours - a period in which traditional numerical weather prediction…
On-Policy Trust Region Policy Optimisation with Replay Buffers
Dmitry Kangin, Nicolas Pugeault
Building upon the recent success of deep reinforcement learning methods, we investigate the possibility of on-policy reinforcement learning improvement by reusing the data from sev…
Aggregated Sparse Attention for Steering Angle Prediction
Sen He, Dmitry Kangin, Yang Mi +1
In this paper, we apply the attention mechanism to autonomous driving for steering angle prediction. We propose the first model, applying the recently introduced sparse attention m…