6 papers
Integrating Contextual Embeddings into Evaluation of Expressive MIDI Piano Performances
Dmitrii Gavrilev, Ilya Borovik, Vladimir Viro
Objective evaluation of expressive MIDI piano performances typically relies on attribute statistics such as timing, velocity, and duration of individual notes. However, these metho…
PianoKontext: Expressive Performance Rendering from Deadpan Context
Dmitrii Gavrilev
Expressive performance rendering (EPR) aims to generate realistic performances constrained on sequences of notes. However, flow matching audio editing models manipulate only synchr…
SyMuPe: Affective and Controllable Symbolic Music Performance
Ilya Borovik, Dmitrii Gavrilev, Vladimir Viro
Emotions are fundamental to the creation and perception of music performances. However, achieving human-like expression and emotion through machine learning models for performance…
ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Mustafa Hajij, Helen Jenne +53
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competi…
Anomaly Detection in Networks via Score-Based Generative Models
Dmitrii Gavrilev, Evgeny Burnaev
Node outlier detection in attributed graphs is a challenging problem for which there is no method that would work well across different datasets. Motivated by the state-of-the-art…
High Performance of Gradient Boosting in Binding Affinity Prediction
Dmitrii Gavrilev, Nurlybek Amangeldiuly, Sergei Ivanov +1
Prediction of protein-ligand (PL) binding affinity remains the key to drug discovery. Popular approaches in recent years involve graph neural networks (GNNs), which are used to lea…