Alexander Immer
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
13
Venues
6
Active years
2019–2025
Best venue rank
A*
Where they publish
Papers
13 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish. | Jan-Matthis Lueckmann, Alexander Immer, Alex Bo-Yuan Chen, Peter H. Li, Mariela D. Petkova, Nirmala A. Iyer, Luuk Willem Hesselink, Aparna Dev, Gudrun Ihrke, Woohyun Park, Alyson Petruncio, Aubrey Weigel, Wyatt Korff, Florian Engert, Jeff Lichtman, Misha B. Ahrens, Michal Januszewski, Viren Jain |
| 2025 | ICLR | Influence Functions for Scalable Data Attribution in Diffusion Models. | Bruno Kacper Mlodozeniec, Runa Eschenhagen, Juhan Bae, Alexander Immer, David Krueger, Richard E. Turner |
| 2024 | ICASSP | Hodge-Aware Contrastive Learning. | Alexander Mllers, Alexander Immer, Vincent Fortuin, Elvin Isufi |
| 2024 | ICLR | Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion. | Alexandru Meterez, Amir Joudaki, Francesco Orabona, Alexander Immer, Gunnar Rtsch, Hadi Daneshmand |
| 2024 | ICML | Improving Neural Additive Models with Bayesian Principles. | Kouroche Bouchiat, Alexander Immer, Hugo Yche, Gunnar Rtsch, Vincent Fortuin |
| 2024 | ICML | Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. | Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, Jos Miguel Hernndez-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rgamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang |
| 2023 | ICML | Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels. | Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rtsch, Bernhard Schlkopf |
| 2023 | ICML | On the Identifiability and Estimation of Causal Location-Scale Noise Models. | Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schlkopf, Peter Bhlmann, Alexander Marx |
| 2022 | ACL | Probing as Quantifying Inductive Bias. | Alexander Immer, Lucas Torroba Hennigen, Vincent Fortuin, Ryan Cotterell |
| 2021 | AISTATS | Improving predictions of Bayesian neural nets via local linearization. | Alexander Immer, Maciej Korzepa, Matthias Bauer |
| 2021 | ICML | Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning. | Alexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rtsch, Mohammad Emtiyaz Khan |
| 2020 | KDD | Sub-Matrix Factorization for Real-Time Vote Prediction. | Alexander Immer, Victor Kristof, Matthias Grossglauser, Patrick Thiran |
| 2019 | ICML | Efficient learning of smooth probability functions from Bernoulli tests with guarantees. | Paul Rolland, Ali Kavis, Alexander Immer, Adish Singla, Volkan Cevher |