Papers, collaborations, and earlier work

arXiv · under review

Prior-amortized in-context Bayesian inference for Generalized Linear Mixed-Effects Models

Alex Kipnis, Marcel Binz, Eric Schulz

arXiv · accepted at Minds and Machines

Measuring what AI systems might do: Towards a measurement science in AI

Konstantinos Voudouris, Mirko Thalmann, Alex Kipnis, José Hernández-Orallo, Eric Schulz

arXiv

A fast neural model for Bayesian mixed-effects regression

Alex Kipnis, Marcel Binz, Eric Schulz

Early metabeta prototype for linear mixed-effects models.

ICLR 2025

A sparse benchmark of reasoning and knowledge in Large Language Models

Alex Kipnis, Konstantinos Voudouris, Luca M. Schulze Buschoff, Eric Schulz

Nature

A foundation model to predict and capture human cognition

Marcel Binz and colleagues, including Alex Kipnis

eLife

Statistical inference on representational geometries

Heiko H. Schütt, Alex Kipnis, Jörn Diedrichsen, Nikolaus Kriegeskorte

This paper incorporates content from my master's thesis.

Neuro-Cognitive Psychology Symposium

Dynamic somatosensory perception and the role of pre-stimulus oscillatory activity

Alex Kipnis, Tilman Stephani, Vadim Nikulin

Neuro-Cognitive Psychology Symposium

Decoding the neural signal of uncertainty in template matching during visual search

Alex Kipnis, Anna Lena Biel, Paul Sauseng

MindBrainBody Symposium

Exploratory analysis of convergence between decomposed ERPs and drift-diffusion model parameters

Alex Kipnis, Anna-Lena Schubert

TeaP

Drifting through the noise: A diffusion model analysis of the interplay between processing and storage in working memory

Jan Göttmann, Alex Kipnis, Gidon Frischkorn, Anna-Lena Schubert