A remark on a paper of Krotov and Hopfield [arXiv:2008.06996]
Not on the map. Why?
Abstract (arXiv)
In their recent paper titled "Large Associative Memory Problem in Neurobiology and Machine Learning" [arXiv:2008.06996] the authors gave a biologically plausible microscopic theory from which one can recover many dense associative memory models discussed in the literature. We show that the layers of the recent "MLP-mixer" [arXiv:2105.01601] as well as the essentially equivalent model in [arXiv:2105.02723] are amongst them.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 5 of its 5 references that are in the map. First posted on arXiv 31 May 2021.
Builds on
5 of 5 references.
References · 5
- 2021MLP-Mixer: An all-MLP Architecture for Visioncited by 1,446
- 2020Hopfield Networks is All You Needcited by 475
- 2016Dense Associative Memory for Pattern Recognitioncited by 236
- 2020Large Associative Memory Problem in Neurobiology and Machine Learningcited by 112
- 2021Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNetcited by 61
Built on by
Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 2; 2025: 3; 2026: 1.
11 papers.
- 2023Energy Transformercited by 71
- 2022Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Modelscited by 55
- 2021Hierarchical Associative Memorycited by 34
- 2022Attention in a family of Boltzmann machines emerging from modern Hopfield networkscited by 7
- 2024Hierarchical Associative Memory, Parallelized MLP-Mixer, and Symmetry Breakingcited by 5
- 2023iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-Mixercited by 3
- 2024Associative memory and dead neuronscited by 1
- 2025Neural Learning Rules from Associative Networks Theorycited by 1
- 2025Classifying States of the Hopfield Network with Improved Accuracy, Generalization, and Interpretabilitycited by 0
- 2025Binding threshold units with artificial oscillatory neuronscited by 0
- 2026Controlled Dynamics Attractor Transformercited by 0
- 2026Controlled Dynamics Attractor Transformer13 Jun 2026
- 2025Binding threshold units with artificial oscillatory neurons6 May 2025
- 2025Neural Learning Rules from Associative Networks Theory11 Mar 2025
- 2025Classifying States of the Hopfield Network with Improved Accuracy, Generalization, and Interpretability4 Mar 2025
- 2024Associative memory and dead neurons2 Oct 2024
- 2024Hierarchical Associative Memory, Parallelized MLP-Mixer, and Symmetry Breaking18 Jun 2024
- 2023iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-Mixer25 Apr 2023
- 2023Energy Transformer14 Feb 2023
- 2022Attention in a family of Boltzmann machines emerging from modern Hopfield networks9 Dec 2022
- 2022Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Models9 Feb 2022
- 2021Hierarchical Associative Memory14 Jul 2021