ML Anthology

Eschenhagen, Runa

13 publications

ICLR 2025 Accelerating Neural Network Training: An Analysis of the AlgoPerf Competition Priya Kasimbeg, Frank Schneider, Runa Eschenhagen, Juhan Bae, Chandramouli Shama Sastry, Mark Saroufim, Boyuan Feng, Less Wright, Edward Z. Yang, Zachary Nado, Sourabh Medapati, Philipp Hennig, Michael Rabbat, George E. Dahl
TMLR 2025 Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs Emilia Magnani, Nicholas Krämer, Runa Eschenhagen, Lorenzo Rosasco, Philipp Hennig
ICLR 2025 Influence Functions for Scalable Data Attribution in Diffusion Models Bruno Kacper Mlodozeniec, Runa Eschenhagen, Juhan Bae, Alexander Immer, David Krueger, Richard E. Turner
NeurIPS 2025 Purifying Shampoo: Investigating Shampoo's Heuristics by Decomposing Its Preconditioner Runa Eschenhagen, Aaron Defazio, Tsung-Hsien Lee, Richard E. Turner, Hao-Jun Michael Shi
ICML 2024 Can We Remove the Square-Root in Adaptive Gradient Methods? a Second-Order Perspective Wu Lin, Felix Dangel, Runa Eschenhagen, Juhan Bae, Richard E. Turner, Alireza Makhzani
ICML 2024 Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC Wu Lin, Felix Dangel, Runa Eschenhagen, Kirill Neklyudov, Agustinus Kristiadi, Richard E. Turner, Alireza Makhzani
NeurIPS 2023 Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures Runa Eschenhagen, Alexander Immer, Richard Turner, Frank Schneider, Philipp Hennig
NeurIPSW 2023 Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC for Large Neural Nets Wu Lin, Felix Dangel, Runa Eschenhagen, Kirill Neklyudov, Agustinus Kristiadi, Richard E. Turner, Alireza Makhzani
NeurIPS 2022 Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks Agustinus Kristiadi, Runa Eschenhagen, Philipp Hennig
NeurIPS 2021 Laplace Redux - Effortless Bayesian Deep Learning Erik Daxberger, Agustinus Kristiadi, Alexander Immer, Runa Eschenhagen, Matthias Bauer, Philipp Hennig
NeurIPS 2020 Continual Deep Learning by Functional Regularisation of Memorable past Pingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard Turner, Mohammad Emtiyaz Khan
ICMLW 2020 Continual Deep Learning by Functional Regularisation of Memorable past Pingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard Turner, Mohammad Emtiyaz Khan
NeurIPS 2019 Practical Deep Learning with Bayesian Principles Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan, Anirudh Jain, Runa Eschenhagen, Richard E Turner, Rio Yokota