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Gregor Bachmann
Gregor Bachmann
PhD student, ETH Zürich
Verified email at inf.ethz.ch
Title
Cited by
Cited by
Year
Constant Curvature Graph Convolutional Networks
G Bachmann, G Bécigneul, O Ganea
International Conference on Machine Learning (ICML 2020), 486-496, 2020
1282020
Surface Defect Classification and Detection on Extruded Aluminum Profiles Using Convolutional Neural Networks
FM Neuhauser, G Bachmann, P Hora
International Journal of Material Forming 13, 591-603, 2020
492020
Precise Characterization of the Prior Predictive Distribution of Deep ReLU Networks
L Noci, G Bachmann, K Roth, S Nowozin, T Hofmann
Advances in Neural Information Processing Systems (NeurIPS 2021), 2021
302021
Analytic Insights into Structure and Rank of Neural Network Hessian Maps
SP Singh, G Bachmann, T Hofmann
Advances in Neural Information Processing Systems (NeurIPS 2021), 2021
252021
Clip-guided vision-language pre-training for question answering in 3d scenes
M Parelli, A Delitzas, N Hars, G Vlassis, S Anagnostidis, G Bachmann, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
172023
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect
L Noci, K Roth, G Bachmann, S Nowozin, T Hofmann
Advances in Neural Information Processing Systems (NeurIPS 2021), 2021
172021
Scaling MLPs: A Tale of Inductive Bias
G Bachmann, S Anagnostidis, T Hofmann
Advances in Neural Information Processing Systems (NeurIPS 2023), 2023
142023
Generalization Through The Lens Of Leave-One-Out Error
G Bachmann, T Hofmann, A Lucchi
International Conference on Learning Representations (ICLR 2022), 2022
132022
Multi-clip: Contrastive vision-language pre-training for question answering tasks in 3d scenes
A Delitzas, M Parelli, N Hars, G Vlassis, S Anagnostidis, G Bachmann, ...
arXiv preprint arXiv:2306.02329, 2023
72023
Uniform Convergence, Adversarial Spheres and a Simple Remedy
G Bachmann, SM Moosavi-Dezfooli, T Hofmann
International Conference on Machine Learning (ICML 2021), 2021
72021
The Curious Case of Benign Memorization
S Anagnostidis, G Bachmann, L Noci, T Hofmann
International Conference on Learning Representations (ICLR 2023), 2022
62022
How Tempering Fixes Data Augmentation in Bayesian Neural Networks
G Bachmann, L Noci, T Hofmann
International Conference on Machine Learning (ICML 2022), 2022
62022
Random Teachers are Good Teachers
F Sarnthein, G Bachmann, S Anagnostidis, T Hofmann
International Conference on Machine Learning (ICML 2023), 2023
52023
The Pitfalls of Next-Token Prediction
G Bachmann, V Nagarajan
arXiv preprint arXiv:2403.06963, 2024
42024
Navigating Scaling Laws: Accelerating Vision Transformer's Training via Adaptive Strategies
S Anagnostidis, G Bachmann, T Hofmann
arXiv preprint arXiv:2311.03233, 2023
22023
Disentangling Linear Mode Connectivity
GS Altıntaş, G Bachmann, L Noci, T Hofmann
UniReps: the First Workshop on Unifying Representations in Neural Models, 2023
12023
EXPLAINTABLE: Explaining Large Scale Models Applied To Tabular Data
JS Baustiste, T Engelmann, NP Montemayor, L Hart, G Lanzillotta, ...
ICLR 2023 Workshop on Trustworthy and Reliable Large-Scale Machine Learning …, 0
1*
A Language Model's Guide Through Latent Space
D von Rütte, S Anagnostidis, G Bachmann, T Hofmann
arXiv preprint arXiv:2402.14433, 2024
2024
How Good is a Single Basin?
K Lion, L Noci, T Hofmann, G Bachmann
AISTATS 2024, 2024
2024
Navigating Scaling Laws: Compute Optimality in Adaptive Model Training
S Anagnostidis, G Bachmann, I Schlag, T Hofmann
Forty-first International Conference on Machine Learning, 0
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Articles 1–20