Workshop
Associative Memory & Hopfield Networks in 2023
Parikshit Ram 路 Hilde Kuehne 路 Daniel Lee 路 Cengiz Pehlevan 路 Mohammed Zaki 路 Lenka Zdeborov谩
Room 223
Fri 15 Dec, 6:15 a.m. PST
This workshop will discuss the latest multidisciplinary developments in Associative Memory and Hopfield Networks. A number of leading researchers in this research area from around the world have already agreed to attend and present their latest results. We anticipate sharing their presentations and outlining future research directions in this emerging field with the rest of the NeurIPS community.
Tagline: We will discuss recent multidisciplinary developments in Hopfield Networks and outline future research directions in this emerging field.
Chat is not available.
Timezone: America/Los_Angeles
Schedule
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Fri 6:15 a.m. - 6:25 a.m.
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Opening Remarks
(
Opening
)
>
SlidesLive Video |
Mohammed Zaki 馃敆 |
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Fri 6:25 a.m. - 6:40 a.m.
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Introductory words on Hopfield Networks
(
Invited Talk
)
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SlidesLive Video |
John J. Hopfield 馃敆 |
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Fri 6:40 a.m. - 7:15 a.m.
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Trading off pattern number and richness: A new associative memory model based on pre-structured low-dimensional manifolds that saturates the information bound regardless of number of memories
(
Invited Talk
)
>
SlidesLive Video |
Ila Fiete 馃敆 |
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Fri 7:15 a.m. - 7:50 a.m.
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Dense Associative Memory for Novel Transformer Architectures
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Invited Talk
)
>
SlidesLive Video |
Dmitry Krotov 馃敆 |
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Fri 7:50 a.m. - 8:00 a.m.
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Rapid Learning without Catastrophic Forgetting in the Morris Water Maze
(
Oral
)
>
link
SlidesLive Video |
Raymond Wang 路 Jaedong Hwang 路 Akhilan Boopathy 路 Ila Fiete 馃敆 |
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Fri 8:00 a.m. - 8:30 a.m.
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Coffee Break
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馃敆 |
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Fri 8:30 a.m. - 8:40 a.m.
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Sequential Learning and Retrieval in a Sparse Distributed Memory: The K-winner Modern Hopfield Network
(
Oral
)
>
link
SlidesLive Video |
Shaunak Bhandarkar 路 James McClelland 馃敆 |
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Fri 8:40 a.m. - 8:50 a.m.
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In search of dispersed memories: Generative diffusion models are associative memory networks
(
Oral
)
>
link
SlidesLive Video |
Luca Ambrogioni 馃敆 |
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Fri 8:50 a.m. - 9:25 a.m.
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Memory Architectures for Deep Learning
(
Invited Talk
)
>
SlidesLive Video |
Sepp Hochreiter 馃敆 |
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Fri 9:25 a.m. - 10:00 a.m.
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The Exponential Capacity of Dense Associative Memories
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Invited Talk
)
>
SlidesLive Video |
Carlo Lucibello 馃敆 |
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Fri 10:00 a.m. - 11:30 a.m.
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Lunch Break
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馃敆 |
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Fri 11:30 a.m. - 12:05 p.m.
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Transformers as the Associative Memory Machines
(
Invited Talk
)
>
SlidesLive Video |
Krzysztof Choromanski 馃敆 |
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Fri 12:05 p.m. - 1:00 p.m.
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Hopfield Networks meet Software Engineering
(
Panel Discussion
)
>
SlidesLive Video |
Blaise Aguera y Arcas 路 Olawale Onabola 路 Bao Pham 路 Benjamin Hoover 路 Hendrik Strobelt 馃敆 |
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Fri 1:00 p.m. - 1:30 p.m.
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Coffee Break
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馃敆 |
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Fri 1:30 p.m. - 1:40 p.m.
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Hopfield Boosting for Out-of-Distribution Detection
(
Oral
)
>
link
SlidesLive Video |
Claus Hofmann 路 Simon Schmid 路 Bernhard Lehner 路 Daniel Klotz 路 Sepp Hochreiter 馃敆 |
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Fri 1:40 p.m. - 1:50 p.m.
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Long Sequence Hopfield Memory
(
Oral
)
>
link
SlidesLive Video |
Hamza Chaudhry 路 Jacob Zavatone-Veth 路 Dmitry Krotov 路 Cengiz Pehlevan 馃敆 |
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Fri 1:50 p.m. - 2:00 p.m.
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Associative Transformer Is A Sparse Representation Learner
(
Oral
)
>
link
SlidesLive Video |
Yuwei Sun 路 Hideya Ochiai 路 Zhirong Wu 路 Stephen Lin 路 Ryota Kanai 馃敆 |
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Fri 2:00 p.m. - 2:10 p.m.
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Retrieving -Nearest Memories with Modern Hopfield Networks
(
Oral
)
>
link
SlidesLive Video |
Alexander Davydov 路 Sean Jaffe 路 Ambuj K Singh 路 Francesco Bullo 馃敆 |
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Fri 2:10 p.m. - 3:25 p.m.
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Poster Session
(
In-person Poster Session
)
>
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馃敆 |
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Fri 3:25 p.m. - 3:30 p.m.
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Closing Remarks
(
Conclusion
)
>
SlidesLive Video |
Parikshit Ram 馃敆 |
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Sparse Modern Hopfield Networks ( Poster ) > link | Andr茅 Martins 路 Vlad Niculae 路 Daniel McNamee 馃敆 |
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Controlling the bifurcations of attractors in modern Hopfield networks ( Poster ) > link | Maria Yampolskaya 路 Pankaj Mehta 馃敆 |
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Associative Transformer Is A Sparse Representation Learner ( Poster ) > link | Yuwei Sun 路 Hideya Ochiai 路 Zhirong Wu 路 Stephen Lin 路 Ryota Kanai 馃敆 |
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Long Sequence Hopfield Memory ( Poster ) > link | Hamza Chaudhry 路 Jacob Zavatone-Veth 路 Dmitry Krotov 路 Cengiz Pehlevan 馃敆 |
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Training a Hopfield Variational Autoencoder with Equilibrium Propagation ( Poster ) > link | Tom Van Der Meersch 路 Johannes Deleu 路 Thomas Demeester 馃敆 |
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In-Context Exemplars as Clues to Retrieving from Large Associative Memory ( Poster ) > link | Jiachen Zhao 馃敆 |
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Enhanced cue associated memory in temporally consistent recurrent neural networks ( Poster ) > link | Udith Haputhanthri 路 Liam Storan 路 Adam Shai 路 Surya Ganguli 路 Mark Schnitzer 路 Hidenori Tanaka 路 Fatih Dinc 馃敆 |
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Learning Sequence Attractors in Recurrent Networks with Hidden Neurons ( Poster ) > link | Yao Lu 路 Si Wu 馃敆 |
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Associative Memory Under the Probabilistic Lens: Improved Transformers & Dynamic Memory Creation ( Poster ) > link | Rylan Schaeffer 路 Mikail Khona 路 Nika Zahedi 路 Ila Fiete 路 Andrey Gromov 路 Sanmi Koyejo 馃敆 |
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In search of dispersed memories: Generative diffusion models are associative memory networks ( Poster ) > link | Luca Ambrogioni 馃敆 |
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Memorization and consolidation in associative memory networks ( Poster ) > link | Danil Tyulmankov 路 Kimberly Stachenfeld 路 Dmitry Krotov 路 L F Abbott 馃敆 |
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Modeling Recognition Memory with Predictive Coding and Hopfield Networks ( Poster ) > link | Tianjin Li 路 Mufeng Tang 路 Rafal Bogacz 馃敆 |
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Associative Memories with Heavy-Tailed Data ( Poster ) > link | Vivien Cabannes 路 Elvis Dohmatob 路 Alberto Bietti 馃敆 |
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Inverse distance weighting attention ( Poster ) > link | Calvin McCarter 馃敆 |
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Modern Hopfield Networks as Memory for Iterative Learning on Tabular Data ( Poster ) > link | Bernhard Sch盲fl 路 Lukas Gruber 路 Angela Bitto 路 Sepp Hochreiter 馃敆 |
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Random Feature Hopfield Networks generalize retrieval to previously unseen examples ( Poster ) > link | Matteo Negri 路 Clarissa Lauditi 路 Gabriele Perugini 路 Carlo Lucibello 路 Enrico Malatesta 馃敆 |
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Retrieving -Nearest Memories with Modern Hopfield Networks ( Poster ) > link | Alexander Davydov 路 Sean Jaffe 路 Ambuj K Singh 路 Francesco Bullo 馃敆 |
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A Different Route to Exponential Storage Capacity ( Poster ) > link | Elvis Dohmatob 馃敆 |
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Variable Memory: Beyond the Fixed Memory Assumption in Memory Modeling ( Poster ) > link | Arjun Karuvally 路 Hava Siegelmann 馃敆 |
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Biologically-inspired adaptive learning in the Hopfield-network based self-optimization model ( Poster ) > link | Aisha Belhadi 馃敆 |
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How Robust Are Energy-Based Models Trained With Equilibrium Propagation? ( Poster ) > link | Siddharth Mansingh 路 Michal Kucer 路 Garrett Kenyon 路 Juston Moore 路 Michael Teti 馃敆 |
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Accelerating Hierarchical Associative Memory: A Deep Equilibrium Approach ( Poster ) > link | C茅dric Goemaere 路 Johannes Deleu 路 Thomas Demeester 馃敆 |
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Sequential Learning and Retrieval in a Sparse Distributed Memory: The K-winner Modern Hopfield Network ( Poster ) > link | Shaunak Bhandarkar 路 James McClelland 馃敆 |
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Energy Transformer ( Poster ) > link | Benjamin Hoover 路 Yuchen Liang 路 Bao Pham 路 Rameswar Panda 路 Hendrik Strobelt 路 Duen Horng Chau 路 Mohammed Zaki 路 Dmitry Krotov 馃敆 |
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Modulating interactions to control dynamics of neural networks ( Poster ) > link | Lukas Herron 路 Pablo Sartori 路 BingKan Xue 馃敆 |
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Generalizable Relational Inference with Cognitive Maps in a Hippocampal Model and in Primates ( Poster ) > link | Jaedong Hwang 路 Sujaya Neupane 路 Mehrdad Jazayeri 路 Ila Fiete 馃敆 |
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Modern Hopfield Network with Local Learning Rules for Class Generalization ( Poster ) > link | Shruti Joshi 路 Giri Prashanth 路 Maksim Bazhenov 馃敆 |
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Rapid Learning without Catastrophic Forgetting in the Morris Water Maze ( Poster ) > link | Raymond Wang 路 Jaedong Hwang 路 Akhilan Boopathy 路 Ila Fiete 馃敆 |
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Multidimensional Hopfield Networks for clustering ( Poster ) > link | Gergely Stomfai 路 艁ukasz Sienkiewicz 路 Barbara Rychalska 馃敆 |
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Statistics-guided Associative Memories ( Poster ) > link | Hongzhi Wang 路 Satyananda Kashyap 路 Niharika DSouza 路 Tanveer Syeda-Mahmood 馃敆 |
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Daydreaming Hopfield Networks and their surprising effectiveness on correlated data ( Poster ) > link | Ludovica Serricchio 路 Claudio Chilin 路 Dario Bocchi 路 Raffaele Marino 路 Matteo Negri 路 Chiara Cammarota 路 Federico Ricci-Tersenghi 馃敆 |
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Hopfield Boosting for Out-of-Distribution Detection ( Poster ) > link | Claus Hofmann 路 Simon Schmid 路 Bernhard Lehner 路 Daniel Klotz 路 Sepp Hochreiter 馃敆 |
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Saliency-Guided Hidden Associative Replay for Continual Learning ( Poster ) > link | Guangji Bai 路 Qilong Zhao 路 Xiaoyang Jiang 路 Liang Zhao 馃敆 |
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Skip Connections Increase the Capacity of Associative Memories in Variable Binding Mechanisms ( Poster ) > link | Yi Xie 路 Yichen Li 路 Akshay Rangamani 馃敆 |
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Minimum Description Length Hopfield Networks ( Poster ) > link | Matan Abudy 路 Nur Lan 路 Emmanuel Chemla 路 Roni Katzir 馃敆 |
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Memory in Plain Sight: A Survey of the Uncanny Resemblances between Diffusion Models and Associative Memories ( Poster ) > link | Benjamin Hoover 路 Hendrik Strobelt 路 Dmitry Krotov 路 Judy Hoffman 路 Zsolt Kira 路 Duen Horng Chau 馃敆 |
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Exploring the Temperature-Dependent Phase Transition in Modern Hopfield Networks ( Poster ) > link | Felix Koulischer 路 C茅dric Goemaere 路 Tom Van Der Meersch 路 Johannes Deleu 路 Thomas Demeester 馃敆 |
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Probabilistic Forecasting via Modern Hopfield Networks ( Poster ) > link | Kashif Rasul 路 Pablo Vicente 路 Anderson Schneider 路 Alexander M盲rz 馃敆 |
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Error-correcting columnar networks: high-capacity memory under sparse connectivity ( Poster ) > link | Haozhe Shan 路 Ludovica Bachschmid-Romano 路 Haim Sompolinsky 馃敆 |
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Hopfield-Enhanced Deep Neural Networks for Artifact-Resilient Brain State Decoding ( Poster ) > link | Arnau Marin-Llobet 路 Arnau Manasanch 路 Mavi Sanchez-Vives 馃敆 |