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Lisa Wimmer
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2020 – today
- 2024
- [c6]Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization. ICLR 2024 - [c5]Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou, Ludwig Bothmann, Bernd Bischl, David Rügamer:
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks? ICML 2024 - [c4]Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer:
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry (Extended Abstract). IJCAI 2024: 8466-8470 - [c3]Amihossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning. ECML/PKDD (1) 2024: 38-55 - [i7]Yusuf Sale, Paul Hofman, Lisa Wimmer, Eyke Hüllermeier, Thomas Nagler:
Second-Order Uncertainty Quantification: Variance-Based Measures. CoRR abs/2401.00276 (2024) - [i6]Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou, Ludwig Bothmann, Bernd Bischl, David Rügamer:
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks? CoRR abs/2402.01484 (2024) - [i5]Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier:
Label-wise Aleatoric and Epistemic Uncertainty Quantification. CoRR abs/2406.02354 (2024) - 2023
- [j1]Ludwig Bothmann, Lisa Wimmer, Omid Charrakh, Tobias Weber, Hendrik Edelhoff, Wibke Peters, Hien Nguyen, Caryl Benjamin, Annette Menzel:
Automated wildlife image classification: An active learning tool for ecological applications. Ecol. Informatics 77: 102231 (2023) - [c2]Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer:
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry. ECML/PKDD (1) 2023: 459-474 - [c1]Lisa Wimmer, Yusuf Sale, Paul Hofman, Bernd Bischl, Eyke Hüllermeier:
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures? UAI 2023: 2282-2292 - [i4]Ludwig Bothmann, Lisa Wimmer, Omid Charrakh, Tobias Weber, Hendrik Edelhoff, Wibke Peters, Hien Nguyen, Caryl Benjamin, Annette Menzel:
Automated wildlife image classification: An active learning tool for ecological applications. CoRR abs/2303.15823 (2023) - [i3]Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer:
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry. CoRR abs/2304.02902 (2023) - [i2]Amirhossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning. CoRR abs/2308.14705 (2023) - [i1]Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Probabilistic Self-supervised Learning via Scoring Rules Minimization. CoRR abs/2309.02048 (2023)
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last updated on 2024-10-21 21:30 CEST by the dblp team
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