3 papers
cs.LG2026
Rethinking Neural Nonlinearity as Gating
Muhammad Sabih, Frank Hannig, Jürgen Teich
Activation functions are considered an essential primitive for neural nonlinearity, i.e., they enable neural networks to serve as universal approximators. In this paper, we show th…
cond-mat.mtrl-sci2026
From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Aritra Roy, Kevin Shen, Andrew MacBride +350
Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…
cs.LG2025
Hardware/Software Co-Design of RISC-V Extensions for Accelerating Sparse DNNs on FPGAs
Muhammad Sabih, Abrarul Karim, Jakob Wittmann +2
The customizability of RISC-V makes it an attractive choice for accelerating deep neural networks (DNNs). It can be achieved through instruction set extensions and corresponding cu…