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David J. Schwab

3 papers here

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

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cond-mat.stat-mech1
  • cs.LG1
  • q-bio.QM1
same name
  • David J. Schwab — 7 papers
  • David J. Schwab — 1 paper, h 6
  • David J. Schwab — 1 paper
  • David J. Schwab — 1 paper
  • David J. Schwab — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedUnderstanding temperature tuning in energy-based models

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

q-bio.QM2025★ 1 cited

Understanding temperature tuning in energy-based models

Peter W Fields, Vudtiwat Ngampruetikorn, David J Schwab +1

Generative models of complex systems often require post-hoc parameter adjustments to produce useful outputs. For example, energy-based models for protein design are sampled at an a…

cond-mat.stat-mech2025

Data coarse graining can improve model performance

Alex Nguyen, David J. Schwab, Vudtiwat Ngampruetikorn

Lossy data transformations by definition lose information. Yet, in modern machine learning, methods like data pruning and lossy data augmentation can help improve generalization pe…

cs.LG2025

When can in-context learning generalize out of task distribution?

Chase Goddard, Lindsay M. Smith, Vudtiwat Ngampruetikorn +1

In-context learning (ICL) is a remarkable capability of pretrained transformers that allows models to generalize to unseen tasks after seeing only a few examples. We investigate em…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.