Viktor Zaverkin

17 papers A* 4Journal 12Unranked 1
YearRankTypeTitle / Venue / Authors
2025 A* conf
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching.
ICML
Federico Errica, Henrik Christiansen, Viktor Zaverkin, Takashi Maruyama, Mathias Niepert, Francesco Alesiani
2025 J jnl
Adaptive Width Neural Networks.
CoRR
Federico Errica, Henrik Christiansen, Viktor Zaverkin, Mathias Niepert, Francesco Alesiani
2025 J jnl
Fast, Modular, and Differentiable Framework for Machine Learning-Enhanced Molecular Simulations.
CoRR
Henrik Christiansen, Takashi Maruyama, Federico Errica, Viktor Zaverkin, Makoto Takamoto, Francesco Alesiani
2025 J jnl
Geometric Kolmogorov-Arnold Superposition Theorem.
CoRR
Francesco Alesiani, Takashi Maruyama, Henrik Christiansen, Viktor Zaverkin
2025 J jnl
Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations.
CoRR
Viktor Zaverkin, Matheus Ferraz, Francesco Alesiani, Mathias Niepert
2025 A* conf
Physics-Informed Weakly Supervised Learning For Interatomic Potentials.
ICML
Makoto Takamoto, Viktor Zaverkin, Mathias Niepert
2025 — conf
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks.
ICML (Position Papers)
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
2025 J jnl
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks.
CoRR
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
2024 A* conf
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing.
NeurIPS
Viktor Zaverkin, Francesco Alesiani, Takashi Maruyama, Federico Errica, Henrik Christiansen, Makoto Takamoto, Nicolas Weber, Mathias Niepert
2024 J jnl
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing.
CoRR
Viktor Zaverkin, Francesco Alesiani, Takashi Maruyama, Federico Errica, Henrik Christiansen, Makoto Takamoto, Nicolas Weber, Mathias Niepert
2024 J jnl
Physics-Informed Weakly Supervised Learning for Interatomic Potentials.
CoRR
Makoto Takamoto, Viktor Zaverkin, Mathias Niepert
2024 A* conf
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks.
ICML
Duy Minh Ho Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert
2024 J jnl
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks.
CoRR
Duy M. H. Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert
2023 J jnl
A Framework and Benchmark for Deep Batch Active Learning for Regression.
J. Mach. Learn. Res.
David Holzmüller, Viktor Zaverkin, Johannes Kästner, Ingo Steinwart
2023 J jnl
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching.
CoRR
Federico Errica, Henrik Christiansen, Viktor Zaverkin, Takashi Maruyama, Mathias Niepert, Francesco Alesiani
2022 J jnl
A Framework and Benchmark for Deep Batch Active Learning for Regression.
CoRR
David Holzmüller, Viktor Zaverkin, Johannes Kästner, Ingo Steinwart
2021 J jnl
Exploration of transferable and uniformly accurate neural network interatomic potentials using optimal experimental design.
Mach. Learn. Sci. Technol.
Viktor Zaverkin, Johannes Kästner