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Erik B. Dam

4 papers hereh-index 439 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.CY1

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CY2026

How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI

Sophia N. Wilson, Sebastian Mair, Mophat Okinyi +3

Large-scale data has fuelled the success of frontier artificial intelligence (AI) models over the past decade. This expansion has relied on sustained efforts by large technology co…

cs.LG2026

Algorithmic Simplification of Neural Networks with Mosaic-of-Motifs

Pedram Bakhtiarifard, Tong Chen, Jonathan Wenshøj +2

Large-scale deep learning models are well-suited for compression. Across a variety of tasks, methods like pruning, quantization, and knowledge distillation have been used to achiev…

cs.LG2026

deCIFer: Crystal Structure Prediction from Powder Diffraction Data using Autoregressive Language Models

Frederik Lizak Johansen, Ulrik Friis-Jensen, Erik Bjørnager Dam +3

Novel materials drive advancements in fields ranging from energy storage to electronics, with crystal structure characterization forming a crucial yet challenging step in materials…

cs.LG2024

PePR: Performance Per Resource Unit as a Metric to Promote Small-Scale Deep Learning in Medical Image Analysis

Raghavendra Selvan, Bob Pepin, Christian Igel +2

The recent advances in deep learning (DL) have been accelerated by access to large-scale data and compute. These large-scale resources have been used to train progressively larger…

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