Bachmann, Gregor

24 publications

CVPR 2025 FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute Sotiris Anagnostidis, Gregor Bachmann, Yeongmin Kim, Jonas Kohler, Markos Georgopoulos, Artsiom Sanakoyeu, Yuming Du, Albert Pumarola, Ali Thabet, Edgar Schönfeld

ICLR 2025 Judge Decoding: Faster Speculative Sampling Requires Going Beyond Model Alignment Gregor Bachmann, Sotiris Anagnostidis, Albert Pumarola, Markos Georgopoulos, Artsiom Sanakoyeu, Yuming Du, Edgar Schönfeld, Ali Thabet, Jonas K Kohler

ICLRW 2024 A Language Model's Guide Through Latent Space Dimitri von Rütte, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann

ICML 2024 A Language Model’s Guide Through Latent Space Dimitri Von Rütte, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann

ICMLW 2024 Feature Learning Dynamics Under Grokking in a Sparse Parity Task Javier Sanguino Bautiste, Gregor Bachmann, Bobby He, Lorenzo Noci, Thomas Hofmann

AISTATS 2024 How Good Is a Single Basin? Kai Lion, Lorenzo Noci, Thomas Hofmann, Gregor Bachmann

ICMLW 2024 Interpolated-MLPs: Controllable Inductive Bias Sean Wu, Jordan Hong, Keybai, Gregor Bachmann

ICML 2024 Navigating Scaling Laws: Compute Optimality in Adaptive Model Training Sotiris Anagnostidis, Gregor Bachmann, Imanol Schlag, Thomas Hofmann

ICML 2024 The Pitfalls of Next-Token Prediction Gregor Bachmann, Vaishnavh Nagarajan

ICLRW 2024 The Pitfalls of Next-Token Prediction Gregor Bachmann, Vaishnavh Nagarajan

CVPRW 2023 CLIP-Guided Vision-Language Pre-Training for Question Answering in 3D Scenes Maria Parelli, Alexandros Delitzas, Nikolas Hars, Georgios Vlassis, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann

NeurIPSW 2023 Disentangling Linear Mode Connectivity Gül Sena Altıntaş, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

ICLRW 2023 Explaintable: Explaining Large Scale Models Applied to Tabular Data Javier Sanguino Bautiste, Tim Engelmann, Natalia Pato Montemayor, Louis Hart, Giulia Lanzillotta, Gregor Bachmann, Thomas Hofmann

NeurIPSW 2023 How Good Is a Single Basin? Kai Lion, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

ICML 2023 Random Teachers Are Good Teachers Felix Sarnthein, Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann

NeurIPS 2023 Scaling MLPs: A Tale of Inductive Bias Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann

ICLR 2023 The Curious Case of Benign Memorization Sotiris Anagnostidis, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

ICLR 2022 Generalization Through the Lens of Leave-One-Out Error Gregor Bachmann, Thomas Hofmann, Aurelien Lucchi

ICML 2022 How Tempering Fixes Data Augmentation in Bayesian Neural Networks Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

NeurIPS 2021 Analytic Insights into Structure and Rank of Neural Network Hessian Maps Sidak Pal Singh, Gregor Bachmann, Thomas Hofmann

NeurIPS 2021 Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann

NeurIPS 2021 Precise Characterization of the Prior Predictive Distribution of Deep ReLU Networks Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann

ICML 2021 Uniform Convergence, Adversarial Spheres and a Simple Remedy Gregor Bachmann, Seyed-Mohsen Moosavi-Dezfooli, Thomas Hofmann

ICML 2020 Constant Curvature Graph Convolutional Networks Gregor Bachmann, Gary Becigneul, Octavian Ganea