148 citations · 316 across the 12 of their papers we have counts for
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cs.LG2026
Dense Structural Compression of Transformers via Gauge-Correct Channel Removal
Jed A. Duersch, Naïm Es-Sebbani, Nathanaël Haas +1
Inference energy per token drives the cost and carbon footprint of deployed transformers. It is dominated by dense matrix products that incur fused multiply-accumulate (FMA) operat…
cs.LG2026
Fourier Transformers for Latent Crystallographic Diffusion and Generative Modeling
Jed A. Duersch, Elohan Veillon, Astrid Klipfel +2
The discovery of new crystalline materials calls for generative models that handle periodic boundary conditions, crystallographic symmetries, and physical constraints, while scalin…