Phil Ostheimer

According to our database1, Phil Ostheimer authored at least 14 papers between 2019 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Skipping the Zeros in Diffusion Models for Sparse Data Generation.
CoRR, May, 2026

2025
DiffStyleTS: Diffusion Model for Style Transfer in Time Series.
CoRR, October, 2025

PIANO: Physics Informed Autoregressive Network.
CoRR, August, 2025

Sparse Data Generation Using Diffusion Models.
CoRR, February, 2025

Challenging Assumptions in Learning Generic Text Style Embeddings.
CoRR, January, 2025

Style Transfer for High-Fidelity Time Series Augmentation.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2025

Tethering Broken Themes: Aligning Neural Topic Models with Labels and Authors.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

BBPOS: BERT-based Part-of-Speech Tagging for Uzbek.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024
SetPINNs: Set-based Physics-informed Neural Networks.
CoRR, 2024

Text Style Transfer Evaluation Using Large Language Models.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023
A Call for Standardization and Validation of Text Style Transfer Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2020
Sentient destination prediction.
User Model. User Adapt. Interact., 2020

2019
A Distributed Modular Scalable and Generic Framework for Parallelizing Population-Based Metaheuristics.
Proceedings of the Parallel Processing and Applied Mathematics, 2019

Superlinear Speedup of Parallel Population-Based Metaheuristics: A Microservices and Container Virtualization Approach.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019


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