Leo Schwinn

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 36

Top Topics

Visual Attention

Diffusion Models

Training Process

Top Venues

Publications

Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space. CoRR (2024)
Björn Nieth, Thomas Altstidl, Leo Schwinn, Björn M. Eskofier
Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation. CoRR (2024)
Leon Götz, Marcel Kollovieh, Stephan Günnemann, Leo Schwinn
Efficient Time Series Processing for Transformers and State-Space Models through Token Merging. CoRR (2024)
Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann
Relaxing Graph Transformers for Adversarial Attacks. CoRR (2024)
Sebastian Schmidt, Leonard Schenk, Leo Schwinn, Stephan Günnemann
A Unified Approach Towards Active Learning and Out-of-Distribution Detection. CoRR (2024)
Philipp Dumbach, Leo Schwinn, Tim Löhr, Phi Long Do, Bjoern M. Eskofier
Artificial intelligence trend analysis on healthcare podcasts using topic modeling and sentiment analysis: a data-driven approach. Evol. Intell. 17 (4) (2024)
Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn
Efficient Adversarial Training in LLMs with Continuous Attacks. CoRR (2024)
Leo Schwinn, Simon Geisler
Revisiting the Robust Alignment of Circuit Breakers. CoRR (2024)
Leo Schwinn, René Raab, An Nguyen, Dario Zanca, Björn M. Eskofier
Exploring misclassifications of robust neural networks to enhance adversarial attacks. Appl. Intell. 53 (17) (2023)
Thomas Altstidl, An Nguyen, Leo Schwinn, Franz Köferl, Christopher Mutschler, Björn M. Eskofier, Dario Zanca
Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks. IJCNN (2023)
Kai Klede, Leo Schwinn, Dario Zanca, Björn M. Eskofier
FastAMI - a Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics. AAAI (2023)
Kai Klede, Leo Schwinn, Dario Zanca, Björn M. Eskofier
FastAMI - a Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics. CoRR (2023)
Thomas Altstidl, David Dobre, Björn M. Eskofier, Gauthier Gidel, Leo Schwinn
Raising the Bar for Certified Adversarial Robustness with Diffusion Models. CoRR (2023)
Leo Schwinn, David Dobre, Stephan Günnemann, Gauthier Gidel
Adversarial Attacks and Defenses in Large Language Models: Old and New Threats. CoRR (2023)
Dario Zanca, Andrea Zugarini, Simon Dietz, Thomas R. Altstidl, Mark A. Turban Ndjeuha, Leo Schwinn, Bjoern M. Eskofier
Contrastive Language-Image Pretrained Models are Zero-Shot Human Scanpath Predictors. CoRR (2023)
Leo Schwinn, David Dobre, Stephan Günnemann, Gauthier Gidel
Adversarial Attacks and Defenses in Large Language Models: Old and New Threats. ICBINB (2023)
Leo Schwinn, Doina Precup, Björn M. Eskofier, Dario Zanca
Behind the Machine's Gaze: Biologically Constrained Neural Networks Exhibit Human-like Visual Attention. CoRR (2022)
Leo Schwinn, Doina Precup, Björn M. Eskofier, Dario Zanca
Simulating Human Gaze with Neural Visual Attention. CoRR (2022)
Leo Schwinn, Doina Precup, Björn M. Eskofier, Dario Zanca
Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention. Trans. Mach. Learn. Res. 2022 (2022)
Leo Schwinn, Leon Bungert, An Nguyen, René Raab, Falk Pulsmeyer, Doina Precup, Bjoern M. Eskofier, Dario Zanca
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification. ICML (2022)
Thomas Altstidl, An Nguyen, Leo Schwinn, Franz Köferl, Christopher Mutschler, Björn M. Eskofier, Dario Zanca
Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks. CoRR (2022)
Johannes Link, Leo Schwinn, Falk Pulsmeyer, Thomas Kautz, Bjoern M. Eskofier
xLength: Predicting Expected Ski Jump Length Shortly after Take-Off Using Deep Learning. Sensors 22 (21) (2022)
Leo Schwinn, Leon Bungert, An Nguyen, René Raab, Falk Pulsmeyer, Doina Precup, Björn M. Eskofier, Dario Zanca
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification. CoRR (2022)
An Nguyen, Stefan Foerstel, Thomas Kittler, Andrey Kurzyukov, Leo Schwinn, Dario Zanca, Tobias Hipp, Da Jun Sun, Michael Schrapp, Eva Rothgang, Björn M. Eskofier
System Design for a Data-Driven and Explainable Customer Sentiment Monitor Using IoT and Enterprise Data. IEEE Access 9 (2021)
Leo Schwinn, An Nguyen, René Raab, Leon Bungert, Daniel Tenbrinck, Dario Zanca, Martin Burger, Bjoern M. Eskofier
Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis. CoRR (2021)
Leo Schwinn, An Nguyen, René Raab, Dario Zanca, Bjoern M. Eskofier, Daniel Tenbrinck, Martin Burger
Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks. IJCNN (2021)
Leo Schwinn, René Raab, An Nguyen, Dario Zanca, Bjoern M. Eskofier
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks. CoRR (2021)
An Nguyen, Stefan Foerstel, Thomas Kittler, Andrey Kurzyukov, Leo Schwinn, Dario Zanca, Tobias Hipp, Da Jun Sun, Michael Schrapp, Eva Rothgang, Bjoern M. Eskofier
System Design for a Data-driven and Explainable Customer Sentiment Monitor. CoRR (2021)
Leon Bungert, René Raab, Tim Roith, Leo Schwinn, Daniel Tenbrinck
CLIP: Cheap Lipschitz Training of Neural Networks. SSVM (2021)
Leo Schwinn, An Nguyen, René Raab, Leon Bungert, Daniel Tenbrinck, Dario Zanca, Martin Burger, Björn M. Eskofier
Identifying untrustworthy predictions in neural networks by geometric gradient analysis. UAI (2021)
Leon Bungert, René Raab, Tim Roith, Leo Schwinn, Daniel Tenbrinck
CLIP: Cheap Lipschitz Training of Neural Networks. CoRR (2021)
An Nguyen, Srijeet Chatterjee, Sven Weinzierl, Leo Schwinn, Martin Matzner, Bjoern M. Eskofier
Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring. ICPM Workshops (2020)
An Nguyen, Wenyu Zhang, Leo Schwinn, Bjoern M. Eskofier
Conformance Checking for a Medical Training Process Using Petri net Simulation and Sequence Alignment. CoRR (2020)
An Nguyen, Srijeet Chatterjee, Sven Weinzierl, Leo Schwinn, Martin Matzner, Bjoern M. Eskofier
Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring. CoRR (2020)
Leo Schwinn, Björn M. Eskofier
Fast and Stable Adversarial Training through Noise Injection. CoRR (2020)
Leo Schwinn, Daniel Tenbrinck, An Nguyen, René Raab, Martin Burger, Bjoern M. Eskofier
Sampled Nonlocal Gradients for Stronger Adversarial Attacks. CoRR (2020)