profileI am a PhD student at the Max Planck ETH Center for Learning Systems advised by Gunnar Rätsch (ETH Zürich) and Bernhard Schölkopf (MPI-IS Tübingen).

My research focuses on probabilistic machine learning and data science.

Currently, I am particularly interested in approximate inference for neural networks and biomedical applications. I want to design algorithms that can incorporate prior knowledge, quantify uncertainty, and automatically select the most likely model given data. Especially in the context of neural networks, these problems remain challenging. I have previously worked on methods for time series, e.g., mobility and political data.

Publications

2020

A Immer, V Kristof, M Grossglauser, P Thiran
KDD, 2020
A Immer, M Korzepa, M Bauer
ICML Uncertainty & Robustness in Deep Learning workshop, 2020
P Pan, S Swaroop, A Immer, R Eschenhagen, R Turner, ME Khan
ICML Continual Learning & Lifelong Learning (spotlight) workshops, 2020

2019

ME Khan, A Immer, E Abedi, M Korzepa
NeurIPS, 2019