Training Variational Autoencoders with Discrete Latent Variables Using Importance Sampling. - Alexander Bartler; Felix Wiewel; Lukas Mauch; Bin Yang 009 (EUSIPCO, 2019)

Continual Learning for Anomaly Detection with Variational Autoencoder. - Felix Wiewel; Bin Yang 009 (ICASSP, 2019)

Localizing Catastrophic Forgetting in Neural Networks. - Felix Wiewel; Bin Yang 009 (CoRR, 2019)

Semi-supervised Riemannian Dimensionality Reduction and Classification Using a Manifold-based Random Walker Graph. - Faezeh Fallah; Felix Wiewel; Bin Yang 009 (EUSIPCO, 2020)

Entropy-based Sample Selection for Online Continual Learning. - Felix Wiewel; Bin Yang 009 (EUSIPCO, 2020)

Continual Learning Through One-Class Classification Using VAE. - Felix Wiewel; Andreas Brendle; Bin Yang 009 (ICASSP, 2020)

Condensed Composite Memory Continual Learning. - Felix Wiewel; Bin Yang 009 (IJCNN, 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 009 (CoRR, 2021)

MT3: Meta Test-Time Training for Self-Supervised Test-Time Adaption. - Alexander Bartler; Andre Bühler; Felix Wiewel; Mario Döbler; Bin Yang 009 (AISTATS, 2022)

TTAPS: Test-Time Adaption by Aligning Prototypes using Self-Supervision. - Alexander Bartler; Florian Bender; Felix Wiewel; Bin Yang 009 (IJCNN, 2022)

Continual Unsupervised Domain Adaptation for Semantic Segmentation using a Class-Specific Transfer. - Robert A. Marsden; Felix Wiewel; Mario Döbler; Yang Yang; Bin Yang 009 (IJCNN, 2022)

Dirichlet Prior Networks for Continual Learning. - Felix Wiewel; Alexander Bartler; Bin Yang 009 (IJCNN, 2022)

Rehearsal-based continual learning with deep neural networks for image classification. - Felix Wiewel (2024)