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An Analysis of Attention via the Lens of Exchangeability and Latent
  Variable Models

An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models

30 December 2022
Yufeng Zhang
Boyi Liu
Qi Cai
Lingxiao Wang
Zhaoran Wang
ArXivPDFHTML

Papers citing "An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models"

9 / 9 papers shown
Title
Deep spatial context: when attention-based models meet spatial
  regression
Deep spatial context: when attention-based models meet spatial regression
Paulina Tomaszewska
El.zbieta Sienkiewicz
Mai P. Hoang
Przemysław Biecek
15
1
0
18 Jan 2024
DF2: Distribution-Free Decision-Focused Learning
DF2: Distribution-Free Decision-Focused Learning
Lingkai Kong
Wenhao Mu
Jiaming Cui
Yuchen Zhuang
B. Prakash
Bo Dai
Chao Zhang
OffRL
33
1
0
11 Aug 2023
A Mechanism for Sample-Efficient In-Context Learning for Sparse
  Retrieval Tasks
A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks
Jacob D. Abernethy
Alekh Agarwal
T. V. Marinov
Manfred K. Warmuth
13
17
0
26 May 2023
A Kernel-Based View of Language Model Fine-Tuning
A Kernel-Based View of Language Model Fine-Tuning
Sadhika Malladi
Alexander Wettig
Dingli Yu
Danqi Chen
Sanjeev Arora
VLM
66
60
0
11 Oct 2022
Relational Reasoning via Set Transformers: Provable Efficiency and
  Applications to MARL
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL
Fengzhuo Zhang
Boyi Liu
Kaixin Wang
Vincent Y. F. Tan
Zhuoran Yang
Zhaoran Wang
OffRL
LRM
49
10
0
20 Sep 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
258
7,412
0
11 Nov 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
172
1,100
0
27 Apr 2021
Zero-Shot Text-to-Image Generation
Zero-Shot Text-to-Image Generation
Aditya A. Ramesh
Mikhail Pavlov
Gabriel Goh
Scott Gray
Chelsea Voss
Alec Radford
Mark Chen
Ilya Sutskever
VLM
253
4,764
0
24 Feb 2021
Representing smooth functions as compositions of near-identity functions
  with implications for deep network optimization
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization
Peter L. Bartlett
S. Evans
Philip M. Long
66
31
0
13 Apr 2018
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