Recurrent Neural Networks (RNNs): A gentle Introduction and Overview. - Robin M. Schmidt (CoRR, 2019)

Collaborative Filtering under Model Uncertainty. - Robin M. Schmidt; Moritz Hahn (CoRR, 2020)

Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers. - Robin M. Schmidt; Frank Schneider 001; Philipp Hennig (ICML, 2021)

Explainability-aided Domain Generalization for Image Classification. - Robin M. Schmidt (CoRR, 2021)

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation. - Kaustubh D. Dhole; Varun Gangal; Sebastian Gehrmann; Aadesh Gupta; Zhenhao Li; Saad Mahamood; Abinaya Mahendiran; Simon Mille; Ashish Srivastava; Samson Tan; Tongshuang Wu; Jascha Sohl-Dickstein; et al. (CoRR, 2021)

Non-Autoregressive Neural Machine Translation: A Call for Clarity. - Robin M. Schmidt; Telmo Pires; Stephan Peitz; Jonas Lööf (EMNLP, 2022)

Learning Language-Specific Layers for Multilingual Machine Translation. - Telmo Pires; Robin M. Schmidt; Yi-Hsiu Liao; Stephan Peitz (ACL (1), 2023)

State Spaces Aren't Enough: Machine Translation Needs Attention. - Ali Vardasbi; Telmo Pessoa Pires; Robin M. Schmidt; Stephan Peitz (EAMT, 2023)