3 papers
cs.LG2026
BitLogic: Training Framework for Gradient-Based FPGA-Native Neural Networks
Simon Bührer, Andreas Plesner, Aczel Till +1
Gradient-based LUT- and logic-gate-based neural networks (LUTNet, LogicNets, DiffLogic, PolyLUT, NeuraLUT, WARP-LUT, DWN, LILogicNet, LightLUT) replace multiply-accumulate arithmet…
cs.CV2026
GIC-DLC: Differentiable Logic Circuits for Hardware-Friendly Grayscale Image Compression
Till Aczel, David F. Jenny, Simon Bührer +3
Neural image codecs achieve higher compression ratios than traditional hand-crafted methods such as PNG or JPEG-XL, but often incur substantial computational overhead, limiting the…
cs.LG2025
Recurrent Deep Differentiable Logic Gate Networks
Simon Bührer, Andreas Plesner, Till Aczel +1
While differentiable logic gates have shown promise in feedforward networks, their application to sequential modeling remains unexplored. This paper presents the first implementati…