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Workshop

Associative Memory & Hopfield Networks in 2023

Parikshit Ram ⋅ Hilde Kuehne ⋅ Daniel Lee ⋅ Cengiz Pehlevan ⋅ Mohammed Zaki ⋅ Lenka Zdeborová
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Abstract

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Schedule

Timezone: America/Los_Angeles
6:15 AM
Opening Remarks
Mohammed Zaki
6:25 AM
Introductory words on Hopfield Networks
John J. Hopfield
7:50 AM
Rapid Learning without Catastrophic Forgetting in the Morris Water Maze
Raymond Wang ⋅ Jaedong Hwang ⋅ Akhilan Boopathy ⋅ Ila Fiete
8:00 AM
Coffee Break
8:50 AM
Memory Architectures for Deep Learning
Sepp Hochreiter
10:00 AM
Lunch Break
11:30 AM
Transformers as the Associative Memory Machines
Krzysztof Choromanski
12:05 PM
Hopfield Networks meet Software Engineering
Blaise Aguera y Arcas ⋅ Olawale Onabola ⋅ Bao Pham ⋅ Benjamin Hoover ⋅ Hendrik Strobelt
1:00 PM
Coffee Break
1:30 PM
Hopfield Boosting for Out-of-Distribution Detection
Claus Hofmann ⋅ Simon Schmid ⋅ Bernhard Lehner ⋅ Daniel Klotz ⋅ Sepp Hochreiter
1:40 PM
Long Sequence Hopfield Memory
Hamza Chaudhry ⋅ Jacob Zavatone-Veth ⋅ Dmitry Krotov ⋅ Cengiz Pehlevan
1:50 PM
Associative Transformer Is A Sparse Representation Learner
Yuwei Sun ⋅ Hideya Ochiai ⋅ Zhirong Wu ⋅ Stephen Lin ⋅ Ryota Kanai
2:00 PM
Retrieving $k$-Nearest Memories with Modern Hopfield Networks
Alexander Davydov ⋅ Sean Jaffe ⋅ Ambuj K Singh ⋅ Francesco Bullo
2:10 PM
Poster Session
3:25 PM
Closing Remarks
Parikshit Ram
Sparse Modern Hopfield Networks
André Martins ⋅ Vlad Niculae ⋅ Daniel McNamee
Associative Transformer Is A Sparse Representation Learner
Yuwei Sun ⋅ Hideya Ochiai ⋅ Zhirong Wu ⋅ Stephen Lin ⋅ Ryota Kanai
Long Sequence Hopfield Memory
Hamza Chaudhry ⋅ Jacob Zavatone-Veth ⋅ Dmitry Krotov ⋅ Cengiz Pehlevan
Training a Hopfield Variational Autoencoder with Equilibrium Propagation
Tom Van Der Meersch ⋅ Johannes Deleu ⋅ Thomas Demeester
Enhanced cue associated memory in temporally consistent recurrent neural networks
Udith Haputhanthri ⋅ Liam Storan ⋅ Adam Shai ⋅ Surya Ganguli ⋅ Mark Schnitzer ⋅ Hidenori Tanaka ⋅ Fatih Dinc
Associative Memory Under the Probabilistic Lens: Improved Transformers & Dynamic Memory Creation
Rylan Schaeffer ⋅ Mikail Khona ⋅ Nika Zahedi ⋅ Ila Fiete ⋅ Andrey Gromov ⋅ Sanmi Koyejo
Memorization and consolidation in associative memory networks
Danil Tyulmankov ⋅ Kimberly Stachenfeld ⋅ Dmitry Krotov ⋅ L F Abbott
Associative Memories with Heavy-Tailed Data
Vivien Cabannes ⋅ Elvis Dohmatob ⋅ Alberto Bietti
Modern Hopfield Networks as Memory for Iterative Learning on Tabular Data
Bernhard Schäfl ⋅ Lukas Gruber ⋅ Angela Bitto ⋅ Sepp Hochreiter
Random Feature Hopfield Networks generalize retrieval to previously unseen examples
Matteo Negri ⋅ Clarissa Lauditi ⋅ Gabriele Perugini ⋅ Carlo Lucibello ⋅ Enrico Malatesta
Retrieving $k$-Nearest Memories with Modern Hopfield Networks
Alexander Davydov ⋅ Sean Jaffe ⋅ Ambuj K Singh ⋅ Francesco Bullo
How Robust Are Energy-Based Models Trained With Equilibrium Propagation?
Siddharth Mansingh ⋅ Michal Kucer ⋅ Garrett Kenyon ⋅ Juston Moore ⋅ Michael Teti
Accelerating Hierarchical Associative Memory: A Deep Equilibrium Approach
Cédric Goemaere ⋅ Johannes Deleu ⋅ Thomas Demeester
Energy Transformer
Benjamin Hoover ⋅ Yuchen Liang ⋅ Bao Pham ⋅ Rameswar Panda ⋅ Hendrik Strobelt ⋅ Duen Horng Chau ⋅ Mohammed Zaki ⋅ Dmitry Krotov
Modulating interactions to control dynamics of neural networks
Lukas Herron ⋅ Pablo Sartori ⋅ BingKan Xue
Generalizable Relational Inference with Cognitive Maps in a Hippocampal Model and in Primates
Jaedong Hwang ⋅ Sujaya Neupane ⋅ Mehrdad Jazayeri ⋅ Ila Fiete
Modern Hopfield Network with Local Learning Rules for Class Generalization
Shruti Joshi ⋅ Giri Prashanth ⋅ Maksim Bazhenov
Rapid Learning without Catastrophic Forgetting in the Morris Water Maze
Raymond Wang ⋅ Jaedong Hwang ⋅ Akhilan Boopathy ⋅ Ila Fiete
Multidimensional Hopfield Networks for clustering
Gergely Stomfai ⋅ Łukasz Sienkiewicz ⋅ Barbara Rychalska
Statistics-guided Associative Memories
Hongzhi Wang ⋅ Satyananda Kashyap ⋅ Niharika DSouza ⋅ Tanveer Syeda-Mahmood
Daydreaming Hopfield Networks and their surprising effectiveness on correlated data
Ludovica Serricchio ⋅ Claudio Chilin ⋅ Dario Bocchi ⋅ Raffaele Marino ⋅ Matteo Negri ⋅ Chiara Cammarota ⋅ Federico Ricci-Tersenghi
Hopfield Boosting for Out-of-Distribution Detection
Claus Hofmann ⋅ Simon Schmid ⋅ Bernhard Lehner ⋅ Daniel Klotz ⋅ Sepp Hochreiter
Saliency-Guided Hidden Associative Replay for Continual Learning
Guangji Bai ⋅ Qilong Zhao ⋅ Xiaoyang Jiang ⋅ Liang Zhao
Minimum Description Length Hopfield Networks
Matan Abudy ⋅ Nur Lan ⋅ Emmanuel Chemla ⋅ Roni Katzir
Memory in Plain Sight: A Survey of the Uncanny Resemblances between Diffusion Models and Associative Memories
Benjamin Hoover ⋅ Hendrik Strobelt ⋅ Dmitry Krotov ⋅ Judy Hoffman ⋅ Zsolt Kira ⋅ Duen Horng Chau
Exploring the Temperature-Dependent Phase Transition in Modern Hopfield Networks
Felix Koulischer ⋅ Cédric Goemaere ⋅ Tom Van Der Meersch ⋅ Johannes Deleu ⋅ Thomas Demeester
Probabilistic Forecasting via Modern Hopfield Networks
Kashif Rasul ⋅ Pablo Vicente ⋅ Anderson Schneider ⋅ Alexander März
Error-correcting columnar networks: high-capacity memory under sparse connectivity
Haozhe Shan ⋅ Ludovica Bachschmid-Romano ⋅ Haim Sompolinsky
Hopfield-Enhanced Deep Neural Networks for Artifact-Resilient Brain State Decoding
Arnau Marin-Llobet ⋅ Arnau Manasanch ⋅ Mavi Sanchez-Vives