65 citations · 71 across the 8 of their papers we have counts for
5 papers · 1 filter
COMIX: Compositional Explanations using Prototypes
Sarath Sivaprasad, Dmitry Kangin, Plamen Angelov +1
Aligning machine representations with human understanding is key to improving interpretability of machine learning (ML) models. When classifying a new image, humans often explain t…
Towards interpretable-by-design deep learning algorithms
Plamen Angelov, Dmitry Kangin, Ziyang Zhang
The proposed framework named IDEAL (Interpretable-by-design DEep learning ALgorithms) recasts the standard supervised classification problem into a function of similarity to a set…
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…
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…