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Ting Chen

29 papers hereh-index 2834.9k citations44 works total

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

author position
  • first author14
  • middle author14
  • last author1

Across the 29 of 29 papers where every author was matched, so the position is known.

fields
  • cs.LG14
  • cs.CV7
  • cs.IR4
  • cs.AI1
  • cs.CL1
  • cs.SI1
same name
  • Ting Chen — 16 papers, h 15
  • Ting Chen — 15 papers, h 9
  • Ting Chen — 13 papers, h 26
  • Ting Chen — 11 papers, h 7
  • Ting Chen — 10 papers, h 9
  • Ting Chen — 6 papers, h 37

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
20162023
most citedA Simple Framework for Contrastive Learning of Visual Representations

7.3k citations · 9.4k across the 29 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.LG2022★ 14 cited

Scalable Adaptive Computation for Iterative Generation

Allan Jabri, David Fleet, Ting Chen

Natural data is redundant yet predominant architectures tile computation uniformly across their input and output space. We propose the Recurrent Interface Networks (RINs), an atten…

cs.CV2022★ 10 cited

A Generalist Framework for Panoptic Segmentation of Images and Videos

Ting Chen, Lala Li, Saurabh Saxena +2

Panoptic segmentation assigns semantic and instance ID labels to every pixel of an image. As permutations of instance IDs are also valid solutions, the task requires learning of hi…

cs.CV2022★ 82 cited

Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning

Ting Chen, Ruixiang Zhang, Geoffrey Hinton

We present Bit Diffusion: a simple and generic approach for generating discrete data with continuous state and continuous time diffusion models. The main idea behind our approach i…

cs.CV2022★ 49 cited

A Unified Sequence Interface for Vision Tasks

Ting Chen, Saurabh Saxena, Lala Li +3

While language tasks are naturally expressed in a single, unified, modeling framework, i.e., generating sequences of tokens, this has not been the case in computer vision. As a res…

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