Viktor Zaverkin

17 papers A* 4Journal 12Unranked 1

Year	Rank	Type	Title / 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