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Discrete and continuous representations and processing in deep learning:
  Looking forward

Discrete and continuous representations and processing in deep learning: Looking forward

AI Open (AO), 2022
4 January 2022
Ruben Cartuyvels
Graham Spinks
Marie-Francine Moens
    OCL
ArXiv (abs)PDFHTML

Papers citing "Discrete and continuous representations and processing in deep learning: Looking forward"

12 / 12 papers shown
Foundations of Artificial Intelligence Frameworks: Notion and Limits of AGI
Foundations of Artificial Intelligence Frameworks: Notion and Limits of AGI
Khanh Gia Bui
NAIAI4CE
412
0
0
23 Nov 2025
Additive Models Explained: A Computational Complexity Approach
Additive Models Explained: A Computational Complexity Approach
Shahaf Bassan
Michal Moshkovitz
Guy Katz
FAtt
291
4
0
24 Oct 2025
Privacy Attack in Federated Learning is Not Easy: An Experimental Study
Privacy Attack in Federated Learning is Not Easy: An Experimental Study
Hangyu Zhu
Liyuan Huang
Zhenping Xie
FedML
322
4
0
28 Sep 2024
Learning to Play Atari in a World of Tokens
Learning to Play Atari in a World of Tokens
Pranav Agarwal
Sheldon Andrews
Samira Ebrahimi Kahou
OffRL
285
6
0
03 Jun 2024
Towards Equipping Transformer with the Ability of Systematic
  Compositionality
Towards Equipping Transformer with the Ability of Systematic CompositionalityAAAI Conference on Artificial Intelligence (AAAI), 2023
Chen Huang
Peixin Qin
Wenqiang Lei
Jiancheng Lv
314
2
0
12 Dec 2023
Computational Natural Philosophy: A Thread from Presocratics through
  Turing to ChatGPT
Computational Natural Philosophy: A Thread from Presocratics through Turing to ChatGPT
G. Dodig-Crnkovic
AI4CELRM
105
1
0
22 Sep 2023
Unbiased Weight Maximization
Unbiased Weight Maximization
Stephen Chung
141
0
0
25 Jul 2023
Can neural networks do arithmetic? A survey on the elementary numerical
  skills of state-of-the-art deep learning models
Can neural networks do arithmetic? A survey on the elementary numerical skills of state-of-the-art deep learning modelsApplied Sciences (Appl. Sci.), 2023
Alberto Testolin
AIMat
274
30
0
14 Mar 2023
Hierarchical Residual Learning Based Vector Quantized Variational
  Autoencoder for Image Reconstruction and Generation
Hierarchical Residual Learning Based Vector Quantized Variational Autoencoder for Image Reconstruction and GenerationBritish Machine Vision Conference (BMVC), 2022
Mohammad Adiban
Kalin Stefanov
Sabato Marco Siniscalchi
G. Salvi
241
12
0
09 Aug 2022
Unconditional Image-Text Pair Generation with Multimodal Cross Quantizer
Unconditional Image-Text Pair Generation with Multimodal Cross QuantizerBritish Machine Vision Conference (BMVC), 2022
Hyungyu Lee
Sungjin Park
Joonseok Lee
Edward Choi
351
4
0
15 Apr 2022
Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing?
  A Structured Review
Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured Review
Kyle Hamilton
Aparna Nayak
Bojan Bozic
Luca Longo
NAI
342
93
0
24 Feb 2022
Do Transformers know symbolic rules, and would we know if they did?
Do Transformers know symbolic rules, and would we know if they did?
Tommi Gröndahl
Yu-Wen Guo
Nirmal Asokan
496
0
0
19 Feb 2022
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