Maximilian Stubbemann

Orcid: 0000-0003-1579-1151

According to our database1, Maximilian Stubbemann authored at least 14 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting.
CoRR, 2024

Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training.
CoRR, 2024

Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research.
CoRR, 2024

ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing.
CoRR, 2024

Moco: A Learnable Meta Optimizer for Combinatorial Optimization.
CoRR, 2024

2023
Orometry, intrinsic dimensionality and learning: Novel insights into network data.
PhD thesis, 2023

Intrinsic Dimension for Large-Scale Geometric Learning.
Trans. Mach. Learn. Res., 2023

Selecting Features by their Resilience to the Curse of Dimensionality.
CoRR, 2023

The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

2022
LG4AV: Combining Language Models and Graph Neural Networks for Author Verification.
Proceedings of the Advances in Intelligent Data Analysis XX, 2022

FCA2VEC: Embedding Techniques for Formal Concept Analysis.
Proceedings of the Complex Data Analytics with Formal Concept Analysis, 2022

2021
Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research.
Scientometrics, 2021

2020
Orometric Methods in Bounded Metric Data.
Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

2019
FCA2VEC: Embedding Techniques for Formal Concept Analysis.
CoRR, 2019


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