Images of desire: food-craving activation during fMRI. - Marcia Levin Pelchat; Andrea Johnson; Robin Chan; Jeffrey Valdez; John Daniel Ragland (NeuroImage, 2004)

The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation. - Robin Chan; Matthias Rottmann; Radin Dardashti; Fabian Hüger; Peter Schlicht; Hanno Gottschalk (CVPR Workshops, 2019)

Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation. - Robin Chan; Matthias Rottmann; Fabian Hüger; Peter Schlicht; Hanno Gottschalk (CoRR, 2019)

MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation. - Robin Chan; Matthias Rottmann; Fabian Hüger; Peter Schlicht; Hanno Gottschalk (CoRR, 2019)

Detection of False Positive and False Negative Samples in Semantic Segmentation. - Matthias Rottmann; Kira Maag; Robin Chan; Fabian Hüger; Peter Schlicht; Hanno Gottschalk (DATE, 2020)

Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. - Robin Chan; Matthias Rottmann; Fabian Hüger; Peter Schlicht; Hanno Gottschalk (IJCNN, 2020)

Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. - Matthias Rottmann; Pascal Colling; Thomas-Paul Hack; Robin Chan; Fabian Hüger; Peter Schlicht; Hanno Gottschalk (IJCNN, 2020)

Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation. - Robin Chan; Matthias Rottmann; Hanno Gottschalk (ICCV, 2021)

SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. - Robin Chan; Krzysztof Lis; Svenja Uhlemeyer; Hermann Blum; Sina Honari; Roland Siegwart; Pascal Fua; Mathieu Salzmann; Matthias Rottmann (NeurIPS Datasets and Benchmarks, 2021)

Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. - Kira Maag; Robin Chan; Svenja Uhlemeyer; Kamil Kowol; Hanno Gottschalk (ACCV (5), 2022)

Detecting and Learning the Unknown in Semantic Segmentation. - Robin Chan; Svenja Uhlemeyer; Matthias Rottmann; Hanno Gottschalk (CoRR, 2022)

Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning. - Julian Burghoff; Robin Chan; Hanno Gottschalk; Annika Mütze; Tobias Riedlinger; Matthias Rottmann; Marius Schubert (CoRR, 2022)

Detecting Anything Overlooked in Semantic Segmentation. - Robin Chan (2022)

Which Spurious Correlations Impact Reasoning in NLI Models? A Visual Interactive Diagnosis through Data-Constrained Counterfactuals. - Robin Chan; Afra Amini; Mennatallah El-Assady (ACL (demo), 2023)

LU-Net: Invertible Neural Networks Based on Matrix Factorization. - Robin Chan; Sarina Penquitt; Hanno Gottschalk (IJCNN, 2023)

What should AI see? Using the public's opinion to determine the perception of an AI. - Robin Chan; Radin Dardashti; Meike Osinski; Matthias Rottmann; Dominik Brüggemann; Cilia Rücker; Peter Schlicht; Fabian Hüger; Nikol Rummel; Hanno Gottschalk (AI Ethics, 2023)

What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages. - Nadav Borenstein; Anej Svete; Robin Chan; Josef Valvoda; Franz Nowak; Isabelle Augenstein; Eleanor Chodroff; Ryan Cotterell (ACL (1), 2024)

On Efficiently Representing Regular Languages as RNNs. - Anej Svete; Robin Chan; Ryan Cotterell (ACL (Findings), 2024)

Adapting LLMs for Structured Natural Language API Integration. - Robin Chan; Katsiaryna Mirylenka; Thomas Gschwind; Christoph Miksovic; Paolo Scotton; Enrico Toniato; Abdel Labbi (EMNLP (Industry Track), 2024)

FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation. - Riza Velioglu; Robin Chan; Barbara Hammer (IJCNN, 2024)

On Affine Homotopy between Language Encoders. - Robin Chan; Reda Boumasmoud; Anej Svete; Yuxin Ren; Qipeng Guo; Zhijing Jin 001; Shauli Ravfogel; Mrinmaya Sachan; Bernhard Schölkopf; Mennatallah El-Assady; Ryan Cotterell (NeurIPS, 2024)

Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes. - Youssef Shoeb; Robin Chan; Gesina Schwalbe; Azarm Nowzad; Fatma Güney; Hanno Gottschalk (WACV, 2024)

New advances in universal approximation with neural networks of minimal width. - Dennis Rochau; Robin Chan; Hanno Gottschalk (CoRR, 2024)

TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models. - Riza Velioglu; Petra Bevandic; Robin Chan; Barbara Hammer (CoRR, 2024)

Enhancing Person-to-Person Virtual Try-On with Multi-Garment Virtual Try-Off. - Riza Velioglu; Petra Bevandic; Robin Chan; Barbara Hammer (CoRR, 2025)