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Using Sparse Semantic Embeddings Learned from Multimodal Text and Image
  Data to Model Human Conceptual Knowledge

Using Sparse Semantic Embeddings Learned from Multimodal Text and Image Data to Model Human Conceptual Knowledge

7 September 2018
Steven Derby
Paul Miller
B. Murphy
Barry Devereux
ArXivPDFHTML

Papers citing "Using Sparse Semantic Embeddings Learned from Multimodal Text and Image Data to Model Human Conceptual Knowledge"

2 / 2 papers shown
Title
VICE: Variational Interpretable Concept Embeddings
VICE: Variational Interpretable Concept Embeddings
Lukas Muttenthaler
C. Zheng
Patrick McClure
Robert A. Vandermeulen
M. Hebart
Francisco Câmara Pereira
24
17
0
02 May 2022
Seeing the advantage: visually grounding word embeddings to better
  capture human semantic knowledge
Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge
Danny Merkx
S. Frank
M. Ernestus
19
4
0
21 Feb 2022
1