Prototype-based Neural Network Layers: Incorporating Vector Quantization. - Sascha Saralajew; Lars Holdijk; Maike Rees; Thomas Villmann (CoRR, 2018)

Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components. - Sascha Saralajew; Lars Holdijk; Maike Rees; Ebubekir Asan; Thomas Villmann (NeurIPS, 2019)

Robustness of Generalized Learning Vector Quantization Models Against Adversarial Attacks. - Sascha Saralajew; Lars Holdijk; Maike Rees; Thomas Villmann (WSOM+, 2019)

Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms. - Sascha Saralajew; Lars Holdijk; Thomas Villmann (NeurIPS, 2020)

Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent. - Priyank Jaini; Lars Holdijk; Max Welling (NeurIPS, 2021)

Path Integral Stochastic Optimal Control for Sampling Transition Paths. - Lars Holdijk; Yuanqi Du; Ferry Hooft; Priyank Jaini; Bernd Ensing; Max Welling (CoRR, 2022)

Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths. - Lars Holdijk; Yuanqi Du; Ferry Hooft; Priyank Jaini; Bernd Ensing; Max Welling (NeurIPS, 2023)