Robin Hesse - RankMe

16 papers A* 3B 1Journal 10Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Accuracy: What Matters in Designing Well-Behaved Image Classification Models? Trans. Mach. Learn. Res. Robin Hesse, Dogukan Bagci, Bernt Schiele, Simone Schaub-Meyer, Stefan Roth
2026	J	`jnl`	What is Missing? Explaining Neurons Activated by Absent Concepts. CoRR Robin Hesse, Simone Schaub-Meyer, Janina Hesse, Bernt Schiele, Stefan Roth
2025	J	`jnl`	Activation Subspaces for Out-of-Distribution Detection. CoRR Baris Zöngür, Robin Hesse, Stefan Roth
2025	J	`jnl`	Beyond Accuracy: What Matters in Designing Well-Behaved Models? CoRR Robin Hesse, Dogukan Bagci, Bernt Schiele, Simone Schaub-Meyer, Stefan Roth
2025	J	`jnl`	Continual Learning Should Move Beyond Incremental Classification. CoRR Rupert Mitchell, Antonio Alliegro, Raffaello Camoriano, Dustin Carrión-Ojeda, Antonio Carta, Georgia Chalvatzaki, Nikhil Churamani, Carlo D'Eramo, Samin Hamidi, Robin Hesse, Fabian Hinder, Roshni Kamath, Vincenzo Lomonaco, Subarnaduti Paul, Francesca Pistilli, Tinne Tuytelaars, Gido M. van de Ven, Kristian Kersting, Simone Schaub-Meyer, Martin Mundt
2025	—	`conf`	Disentangling Polysemantic Channels in Convolutional Neural Networks. CVPR Workshops Robin Hesse, Jonas Fischer, Simone Schaub-Meyer, Stefan Roth
2025	J	`jnl`	Disentangling Polysemantic Channels in Convolutional Neural Networks. CoRR Robin Hesse, Jonas Fischer, Simone Schaub-Meyer, Stefan Roth
2024	A*	`conf`	Benchmarking the Attribution Quality of Vision Models. NeurIPS Robin Hesse, Simone Schaub-Meyer, Stefan Roth
2024	J	`jnl`	Benchmarking the Attribution Quality of Vision Models. CoRR Robin Hesse, Simone Schaub-Meyer, Stefan Roth
2023	—	`conf`	Content-Adaptive Downsampling in Convolutional Neural Networks. CVPR Workshops Robin Hesse, Simone Schaub-Meyer, Stefan Roth
2023	J	`jnl`	Content-Adaptive Downsampling in Convolutional Neural Networks. CoRR Robin Hesse, Simone Schaub-Meyer, Stefan Roth
2023	A*	`conf`	FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods. ICCV Robin Hesse, Simone Schaub-Meyer, Stefan Roth
2023	J	`jnl`	FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods. CoRR Robin Hesse, Simone Schaub-Meyer, Stefan Roth
2021	A*	`conf`	Fast Axiomatic Attribution for Neural Networks. NeurIPS Robin Hesse, Simone Schaub-Meyer, Stefan Roth
2021	J	`jnl`	Fast Axiomatic Attribution for Neural Networks. CoRR Robin Hesse, Simone Schaub-Meyer, Stefan Roth
2016	B	`conf`	Efficient Verification of Program Fragments: Eager POR. ATVA Patrick Metzler, Habib Saissi, Péter Bokor, Robin Hesse, Neeraj Suri