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Adam S. Charles

9 papers hereh-index 181.2k citations54 works total

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

author position
  • sole author1
  • middle author3
  • last author5

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • stat.ML3
  • cs.LG2
  • cs.CL1
  • eess.IV1
  • eess.SP1
  • stat.AP1
same name
  • Adam S. Charles — 5 papers, h 3
  • Adam S. Charles — 3 papers, h 2
  • Adam S. Charles — 3 papers, h 2
  • Adam S. Charles — 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

activity
20182023
most citedProspective Learning: Principled Extrapolation to the Future

6 citations · 14 across the 6 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CL2022

Multi-Lingual DALL-E Storytime

Noga Mudrik, Adam S. Charles

While recent advancements in artificial intelligence (AI) language models demonstrate cutting-edge performance when working with English texts, equivalent models do not exist in ot…

stat.ML2022★ 5 cited

Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics

Noga Mudrik, Yenho Chen, Eva Yezerets +2

Learning interpretable representations of neural dynamics at a population level is a crucial first step to understanding how observed neural activity relates to perception and beha…

eess.IV2022★ 2 cited

Data Processing of Functional Optical Microscopy for Neuroscience

Hadas Benisty, Alexander Song, Gal Mishne +1

Functional optical imaging in neuroscience is rapidly growing with the development of new optical systems and fluorescence indicators. To realize the potential of these massive spa…

cs.LG2022★ 6 cited

Prospective Learning: Principled Extrapolation to the Future

Ashwin De Silva, Rahul Ramesh, Lyle Ungar +40

Learning is a process which can update decision rules, based on past experience, such that future performance improves. Traditionally, machine learning is often evaluated under the…

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