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Representation Learning via Manifold Flattening and Reconstruction

Representation Learning via Manifold Flattening and Reconstruction

2 May 2023
Michael Psenka
Druv Pai
Vishal Raman
S. Sastry
Y. Ma
ArXivPDFHTML

Papers citing "Representation Learning via Manifold Flattening and Reconstruction"

6 / 6 papers shown
Title
Latent Manifold Reconstruction and Representation with Topological and Geometrical Regularization
Latent Manifold Reconstruction and Representation with Topological and Geometrical Regularization
Ren Wang
Pengcheng Zhou
39
0
0
07 May 2025
Geometric Signatures of Compositionality Across a Language Model's Lifetime
Geometric Signatures of Compositionality Across a Language Model's Lifetime
Jin Hwa Lee
Thomas Jiralerspong
Lei Yu
Yoshua Bengio
Emily Cheng
CoGe
84
0
0
02 Oct 2024
Emergence of a High-Dimensional Abstraction Phase in Language Transformers
Emergence of a High-Dimensional Abstraction Phase in Language Transformers
Emily Cheng
Diego Doimo
Corentin Kervadec
Iuri Macocco
Jade Yu
A. Laio
Marco Baroni
112
11
0
24 May 2024
Sampling is as easy as learning the score: theory for diffusion models
  with minimal data assumptions
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
Sitan Chen
Sinho Chewi
Jungshian Li
Yuanzhi Li
Adil Salim
Anru R. Zhang
DiffM
135
248
0
22 Sep 2022
On the Principles of Parsimony and Self-Consistency for the Emergence of
  Intelligence
On the Principles of Parsimony and Self-Consistency for the Emergence of Intelligence
Y. Ma
Doris Y. Tsao
H. Shum
67
75
0
11 Jul 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
308
7,457
0
11 Nov 2021
1