Runa Eschenhagen
9 papers · 2019–2025 · 3 conferences · across top CS/AI conferences
Achievements
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π Cross-Pollinator (15) π Conference Polyglot (3) π Academic Marathon (6) πΊοΈ Taxonomy Completionist (14) π§ Keyword Pioneer
π
Interdisciplinary Bridge
π₯
Unstoppable
(7)
β
The Questioner
Conferences
NIPS (5)
ICLR (2)
ICML (2)
Top co-authors
Keywords
variational inference
(3)
bayesian deep learning
(2)
continual learning
(2)
neural network training
(1)
hyperparameter optimization
(1)
uncertainty quantification
(1)
laplace approximation
(1)
gaussian process
(1)
weight regularization
(1)
monte carlo integration
(1)
posterior approximation
(1)
hamiltonian monte carlo
(1)
second-order optimization
(1)
normalizing flow
(1)
bayesian neural network
(1)
deep network
(1)
predictive uncertainty
(1)
hyperparameter selection
(1)
functional regularization
(1)
kronecker-factored approximate curvature
(1)
Papers
Accelerating neural network training: An analysis of the AlgoPerf competition
ICLR 2025
Influence Functions for Scalable Data Attribution in Diffusion Models
ICLR 2025
Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC
ICML 2024
Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective
ICML 2024
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
NIPS 2023
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
NIPS 2022
Laplace Redux - Effortless Bayesian Deep Learning
NIPS 2021
Continual Deep Learning by Functional Regularisation of Memorable Past
NIPS 2020
Practical Deep Learning with Bayesian Principles
NIPS 2019