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ORCIDMaksim Zhdanov 0001
Person information
- affiliation: University of Amsterdam, Institute of Informatics, AMLab, Amsterdam, The Netherlands
- affiliation: Helmholtz AI, Dresden, Germany
- affiliation: TU Dresden, HZDR, Dresden, Germany
Other persons with the same name
- Maksim Zhdanov 0002
![[0009-0009-1444-4933]](https://dblp.org/img/orcid-mark.12x12.png "0009-0009-1444-4933")
— AIRI, Moscow, Russia (and 1 more)
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2020 – today
- 2026
[i15]Maksim Zhdanov, Ana Lucic, Max Welling, Jan-Willem van de Meent:
(Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models. CoRR abs/2604.16429 (2026)- [i14]Pedro M. P. Curvo, Maksim Zhdanov, Floor Eijkelboom, Jan-Willem van de Meent:
Follow the Mean: Reference-Guided Flow Matching. CoRR abs/2605.10302 (2026) - [i13]Olga Zaghen, Maksim Zhdanov, Dario Coscia, David R. Wessels, Erik J. Bekkers:
Uncertainty-aware Machine Learning Interatomic Potentials via Learned Functional Perturbations. CoRR abs/2605.19939 (2026) - [i12]David R. Wessels, Farhad Ramezanghorbani, David W. Romero, Alireza Moradzadeh, Olivia Viessmann, Maksim Zhdanov, John St. John, Ken Janik, David M. Knigge, Yucheng Tang, Erik J. Bekkers, Saee Gopal Paliwal:
Native Multi-Dimensional Subquadratic Operators via Input Dependent Long Convolutions. CoRR abs/2607.19378 (2026) - 2025
- [j1]Winfried van den Dool, Maksim Zhdanov, Yuki M. Asano, Max Welling:
Adaptive Mesh Quantization for Neural PDE Solvers. Trans. Mach. Learn. Res. 2025 (2025) - [c5]Maksim Zhdanov, Max Welling, Jan-Willem van de Meent:
Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems. ICML 2025 - [i11]Maksim Zhdanov, Max Welling, Jan-Willem van de Meent:
Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems. CoRR abs/2502.17019 (2025) - [i10]Maksim Zhdanov, Nabil Iqbal, Erik J. Bekkers, Patrick Forré:
AdS-GNN - a Conformally Equivariant Graph Neural Network. CoRR abs/2505.12880 (2025) - [i9]Catalin E. Brita, Hieu Nguyen, Lohithsai Yadala Chanchu, Domonkos Nagy, Maksim Zhdanov:
BSA: Ball Sparse Attention for Large-scale Geometries. CoRR abs/2506.12541 (2025) - [i8]Bálint László Szarvas, Maksim Zhdanov:
Conditional Clifford-Steerable CNNs with Complete Kernel Basis for PDE Modeling. CoRR abs/2510.14007 (2025) - [i7]Winfried van den Dool, Maksim Zhdanov, Yuki M. Asano, Max Welling:
Adaptive Mesh-Quantization for Neural PDE Solvers. CoRR abs/2511.18474 (2025) - [i6]Pedro M. P. Curvo, Jan-Willem van de Meent, Maksim Zhdanov:
MSPT: Efficient Large-Scale Physical Modeling via Parallelized Multi-Scale Attention. CoRR abs/2512.01738 (2025) - 2024
- [c4]Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré:
Clifford-Steerable Convolutional Neural Networks. ICML 2024: 61203-61228 - [i5]Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré:
Clifford-Steerable Convolutional Neural Networks. CoRR abs/2402.14730 (2024) - 2023
- [c3]Maksim Zhdanov, Nico Hoffmann, Gabriele Cesa:
Implicit Convolutional Kernels for Steerable CNNs. NeurIPS 2023 - 2022
- [c2]Maksim Zhdanov, Saskia Steinmann, Nico Hoffmann:
Investigating Brain Connectivity with Graph Neural Networks and GNNExplainer. ICPR 2022: 5155-5161 - [c1]Maksim Zhdanov, Saskia Steinmann, Nico Hoffmann:
Learning Generative Factors of EEG Data with Variational Auto-Encoders. DGM4MICCAI@MICCAI 2022: 45-54 - [i4]Maksim Zhdanov, Saskia Steinmann, Nico Hoffmann:
Investigating Brain Connectivity with Graph Neural Networks and GNNExplainer. CoRR abs/2206.01930 (2022) - [i3]Maksim Zhdanov, Saskia Steinmann, Nico Hoffmann:
Learning Generative Factors of Neuroimaging Data with Variational auto-encoders. CoRR abs/2206.01939 (2022) - [i2]Maksim Zhdanov, Lisa Randolph, Thomas Kluge, Motoaki Nakatsutsumi, Christian Gutt, Marina Ganeva, Nico Hoffmann:
Amortized Bayesian Inference of GISAXS Data with Normalizing Flows. CoRR abs/2210.01543 (2022) - [i1]Maksim Zhdanov, Nico Hoffmann, Gabriele Cesa:
Implicit Neural Convolutional Kernels for Steerable CNNs. CoRR abs/2212.06096 (2022)
Coauthor Index
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