Alexander Bartler

According to our database, Alexander Bartler authored at least 11 papers between 2018 and 2024.

Collaborative distances:

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

2024

Prompt tuning for parameter-efficient medical image segmentation.

Marc Fischer, Alexander Bartler, Bin Yang

Medical Image Anal., January, 2024

2022

Dirichlet Prior Networks for Continual Learning.

Felix Wiewel, Alexander Bartler, Bin Yang

Proceedings of the International Joint Conference on Neural Networks, 2022

Contrastive Learning and Self-Training for Unsupervised Domain Adaptation in Semantic Segmentation.

Robert A. Marsden, Alexander Bartler, Mario Döbler, Bin Yang

Proceedings of the International Joint Conference on Neural Networks, 2022

TTAPS: Test-Time Adaption by Aligning Prototypes using Self-Supervision.

Alexander Bartler, Florian Bender, Felix Wiewel, Bin Yang

Proceedings of the International Joint Conference on Neural Networks, 2022

MT3: Meta Test-Time Training for Self-Supervised Test-Time Adaption.

Alexander Bartler, Andre Bühler, Felix Wiewel, Mario Döbler, Bin Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Estimation of Bivariate Structural Causal Models by Variational Gaussian Process Regression Under Likelihoods Parametrised by Normalising Flows.

Nico Reick, Felix Wiewel, Alexander Bartler, Bin Yang

CoRR, 2021

Anomaly Detection Based on Selection and Weighting in Latent Space.

Yiwen Liao, Alexander Bartler, Bin Yang

Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

2020

Grad-LAM: Visualization of Deep Neural Networks for Unsupervised Learning.

Alexander Bartler, Darius Hinderer, Bin Yang

Proceedings of the 28th European Signal Processing Conference, 2020

2019

Prediction of FDG uptake in Lung Tumors from CT Images Using Generative Adversarial Networks.

Annika Liebgott, Darius Hinderer, Karim Armanious, Alexander Bartler, Konstantin Nikolaou, Sergios Gatidis, Bin Yang

Proceedings of the 27th European Signal Processing Conference, 2019

Training Variational Autoencoders with Discrete Latent Variables Using Importance Sampling.

Alexander Bartler, Felix Wiewel, Lukas Mauch, Bin Yang

Proceedings of the 27th European Signal Processing Conference, 2019

2018

Automated Detection of Solar Cell Defects with Deep Learning.

Alexander Bartler, Lukas Mauch, Bin Yang, Michael Reuter, Liviu Stoicescu

Proceedings of the 26th European Signal Processing Conference, 2018