Robin Chan

According to our database, Robin Chan authored at least 22 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

On Affine Homotopy between Language Encoders.

Robin Chan, Reda Boumasmoud, Anej Svete, Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Mennatallah El-Assady, Ryan Cotterell

CoRR, 2024

FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation.

Riza Velioglu, Robin Chan, Barbara Hammer

Proceedings of the International Joint Conference on Neural Networks, 2024

Adapting LLMs for Structured Natural Language API Integration.

Robin Chan, Katsiaryna Mirylenka, Thomas Gschwind, Christoph Miksovic, Paolo Scotton, Enrico Toniato, Abdel Labbi

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

On Efficiently Representing Regular Languages as RNNs.

Anej Svete, Robin Chan, Ryan Cotterell

Proceedings of the Findings of the Association for Computational Linguistics, 2024

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

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

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, November, 2023

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

CoRR, 2023

LU-Net: Invertible Neural Networks Based on Matrix Factorization.

Robin Chan, Sarina Penquitt, Hanno Gottschalk

Proceedings of the International Joint Conference on Neural Networks, 2023

Which Spurious Correlations Impact Reasoning in NLI Models? A Visual Interactive Diagnosis through Data-Constrained Counterfactuals.

Robin Chan, Afra Amini, Mennatallah El-Assady

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2023

2022

Detecting Anything Overlooked in Semantic Segmentation.

Robin Chan

PhD thesis, 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 and Learning the Unknown in Semantic Segmentation.

Robin Chan, Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk

CoRR, 2022

Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects.

Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk

Proceedings of the Computer Vision - ACCV 2022, 2022

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

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation.

Robin Chan, Matthias Rottmann, Hanno Gottschalk

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

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

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Controlled False Negative Reduction of Minority Classes in Semantic Segmentation.

Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Detection of False Positive and False Negative Samples in Semantic Segmentation.

Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

2019

MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation.

Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk

CoRR, 2019

Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation.

Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk

CoRR, 2019

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

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2004

Images of desire: food-craving activation during fMRI.

Marcia Levin Pelchat, Andrea Johnson, Robin Chan, Jeffrey Valdez, John Daniel Ragland

NeuroImage, 2004