Ilia Igashov

17 papers A* 4Journal 11Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Flow-Based Fragment Identification via Binding Site-Specific Latent Representations.
CoRR
Rebecca M. Neeser, Ilia Igashov, Arne Schneuing, Michael M. Bronstein, Philippe Schwaller, Bruno E. Correia
2025 A* conf
Multi-domain Distribution Learning for De Novo Drug Design.
ICLR
Arne Schneuing, Ilia Igashov, Adrian W. Dobbelstein, Thomas Castiglione, Michael M. Bronstein, Bruno Correia
2025 J jnl
Multi-domain Distribution Learning for De Novo Drug Design.
CoRR
Arne Schneuing, Ilia Igashov, Adrian W. Dobbelstein, Thomas Castiglione, Michael M. Bronstein, Bruno E. Correia
2025 A* conf
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints.
ICLR
Miruna T. Cretu, Charles Harris, Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Bruno E. Correia, Julien Roy, Emmanuel Bengio, Pietro Lio
2024 J jnl
Equivariant 3D-conditional diffusion model for molecular linker design.
Nat. Mac. Intell.
Ilia Igashov, Hannes Stärk, Clément Vignac, Arne Schneuing, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia
2024 A* conf
RetroBridge: Modeling Retrosynthesis with Markov Bridges.
ICLR
Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia
2024 J jnl
Structure-based drug design with equivariant diffusion models.
Nat. Comput. Sci.
Arne Schneuing, Charles Harris, Yuanqi Du, Kieran Didi, Arian Rokkum Jamasb, Ilia Igashov, Weitao Du, Carla P. Gomes, Tom L. Blundell, Pietro Lio, Max Welling, Michael M. Bronstein, Bruno E. Correia
2023 J jnl
RetroBridge: Modeling Retrosynthesis with Markov Bridges.
CoRR
Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia
2023 — conf
The Second Learning on Graphs Conference: Preface.
LoG
Soledad Villar, Benjamin Paul Chamberlain, Yuanqi Du, Hannes Stärk, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan
2022 A* conf
6DCNN with Roto-Translational Convolution Filters for Volumetric Data Processing.
AAAI
Dmitrii Zhemchuzhnikov, Ilia Igashov, Sergei Grudinin
2022 J jnl
Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design.
CoRR
Ilia Igashov, Hannes Stärk, Clément Vignac, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia
2022 J jnl
Structure-based Drug Design with Equivariant Diffusion Models.
CoRR
Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom L. Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael M. Bronstein, Bruno E. Correia
2022 — conf
The First Learning on Graphs Conference: Preface.
LoG
Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov
2021 J jnl
6DCNN with roto-translational convolution filters for volumetric data processing.
CoRR
Dmitrii Zhemchuzhnikov, Ilia Igashov, Sergei Grudinin
2021 J jnl
Spherical convolutions on molecular graphs for protein model quality assessment.
Mach. Learn. Sci. Technol.
Ilia Igashov, Nikita Pavlichenko, Sergei Grudinin
2021 J jnl
VoroCNN: deep convolutional neural network built on 3D Voronoi tessellation of protein structures.
Bioinform.
Ilia Igashov, Kliment Olechnovic, Maria Kadukova, Ceslovas Venclovas, Sergei Grudinin
2020 J jnl
Spherical convolutions on molecular graphs for protein model quality assessment.
CoRR
Ilia Igashov, Nikita Pavlichenko, Sergei Grudinin