1 citations · 1 across the 4 of their papers we have counts for
5 papers
Multiple Token Divergence: Measuring and Steering In-Context Computation Density
Vincent Herrmann, Eric Alcaide, Michael Wand +1
Measuring the in-context computational effort of language models is a key challenge, as metrics like next-token loss fail to capture reasoning complexity. Prior methods based on la…
Space Explanations of Neural Network Classification
Faezeh Labbaf, Tomáš Kolárik, Martin Blicha +3
We present a novel logic-based concept called Space Explanations for classifying neural networks that gives provable guarantees of the behavior of the network in continuous areas o…
Direct Molecular Polarizability Prediction with SO(3) Equivariant Local Frame GNNs
Jean Philip Filling, Felix Post, Michael Wand +1
We introduce a novel equivariant graph neural network (GNN) architecture designed to predict the tensorial response properties of molecules. Unlike traditional frameworks that focu…
Fast and scalable retrosynthetic planning with a transformer neural network and speculative beam search
Mikhail Andronov, Natalia Andronova, Michael Wand +2
AI-based computer-aided synthesis planning (CASP) systems are in demand as components of AI-driven drug discovery workflows. However, the high latency of such CASP systems limits t…
ResNets Are Deeper Than You Think
Christian H. X. Ali Mehmeti-Göpel, Michael Wand
Residual connections remain ubiquitous in modern neural network architectures nearly a decade after their introduction. Their widespread adoption is often credited to their dramati…