3 papers
cs.LG2026
Building Better Activation Oracles
Jan Bauer, Celeste De Schamphelaere, Adam Karvonen +2
Activation Oracles (AOs) are promising methods for interpreting residual stream activations. However, current AOs face important issues, such as hallucinations and vagueness. Addit…
q-bio.NC2026
Discrete signaling mediates chaotic regularization in recurrent neural networks
Jan Bauer, Christian Keup, Jonathan Kadmon +1
Cortical circuits operate in a regime of intrinsic chaos, where even tiny changes in input can lead to divergent neural responses. Yet, remarkably, population codes in the brain va…
cs.LG2026
A unified theory of feature learning in RNNs and DNNs
Jan P. Bauer, Kirsten Fischer, Moritz Helias +1
Recurrent and deep neural networks (RNNs/DNNs) are cornerstone architectures in machine learning. Remarkably, RNNs differ from DNNs only by weight sharing, as can be shown through…