Imant Daunhawer

According to our database, Imant Daunhawer authored at least 12 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Benchmarking the Fairness of Image Upsampling Methods.

Mike Laszkiewicz, Imant Daunhawer, Julia E. Vogt, Asja Fischer, Johannes Lederer

CoRR, 2024

2023

Multimodal Representation Learning under Weak Supervision.

Imant Daunhawer

PhD thesis, 2023

How robust is unsupervised representation learning to distribution shift?

Yuge Shi, Imant Daunhawer, Julia E. Vogt, Philip H. S. Torr, Amartya Sanyal

Proceedings of the Eleventh International Conference on Learning Representations, 2023

MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises.

Emanuele Palumbo, Imant Daunhawer, Julia E. Vogt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Identifiability Results for Multimodal Contrastive Learning.

Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx, Julia E. Vogt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

How robust are pre-trained models to distribution shift?

Yuge Shi, Imant Daunhawer, Julia E. Vogt, Philip H. S. Torr, Amartya Sanyal

CoRR, 2022

On the Limitations of Multimodal VAEs.

Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E. Vogt

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Generalized Multimodal ELBO.

Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt

Proceedings of the 9th International Conference on Learning Representations, 2021

Decoupling State Representation Methods from Reinforcement Learning in Car Racing.

Juan M. Montoya, Imant Daunhawer, Julia E. Vogt, Marco A. Wiering

Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021

2020

Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence.

Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

PET-Guided Attention Network for Segmentation of Lung Tumors from PET/CT Images.

Varaha Karthik Pattisapu, Imant Daunhawer, Thomas J. Weikert, Alexander Sauter, Bram Stieltjes, Julia E. Vogt

Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020

Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models.

Imant Daunhawer, Thomas M. Sutter, Ricards Marcinkevics, Julia E. Vogt

Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020