NeurIPS 2023 Workshop AMHN Submissions

Biologically-inspired adaptive learning in the Hopfield-network based self-optimization model
Aisha Belhadi
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Enhanced cue associated memory in temporally consistent recurrent neural networks
Udith Haputhanthri, Liam Storan, Adam Shai, Surya Ganguli, Mark Schnitzer, Hidenori Tanaka, Fatih Dinc
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Minimum Description Length Hopfield Networks
Matan Abudy, Nur Lan, Emmanuel Chemla, Roni Katzir
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Associative Transformer Is A Sparse Representation Learner
Yuwei Sun, Hideya Ochiai, Zhirong Wu, Stephen Lin, Ryota Kanai
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Oral
- Readers: Everyone
Hopfield Boosting for Out-of-Distribution Detection
Claus Hofmann, Simon Lucas Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Oral
- Readers: Everyone
Modern Hopfield Network with Local Learning Rules for Class Generalization
Shruti A Joshi, Giri Prashanth, Maksim Bazhenov
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Saliency-Guided Hidden Associative Replay for Continual Learning
Guangji Bai, Qilong Zhao, Xiaoyang Jiang, Liang Zhao
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
In-Context Exemplars as Clues to Retrieving from Large Associative Memory
Jiachen ZHAO
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Hopfield-Enhanced Deep Neural Networks for Artifact-Resilient Brain State Decoding
Arnau Marin-Llobet, Arnau Manasanch, Maria V. Sanchez Vives
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Sequential Learning and Retrieval in a Sparse Distributed Memory: The K-winner Modern Hopfield Network
Shaunak Bhandarkar, James Lloyd McClelland
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Oral
- Readers: Everyone
Rapid Learning without Catastrophic Forgetting in the Morris Water Maze
Raymond Wang, Jaedong Hwang, Akhilan Boopathy, Ila R Fiete
- Published: 27 Oct 2023, Last Modified: 03 Dec 2023
- AMHN23 Oral
- Readers: Everyone
Accelerating Hierarchical Associative Memory: A Deep Equilibrium Approach
Cédric Goemaere, Johannes Deleu, Thomas Demeester
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Retrieving $k$-Nearest Memories with Modern Hopfield Networks
Alexander Davydov, Sean Jaffe, Ambuj Singh, Francesco Bullo
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Oral
- Readers: Everyone
Random Feature Hopfield Networks generalize retrieval to previously unseen examples
Matteo Negri, Clarissa Lauditi, Gabriele Perugini, Carlo Lucibello, Enrico Maria Malatesta
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Probabilistic Forecasting via Modern Hopfield Networks
Kashif Rasul, Pablo Vicente, Anderson Schneider, Alexander März
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Energy Transformer
Benjamin Hoover, Yuchen Liang, Bao Pham, Rameswar Panda, Hendrik Strobelt, Duen Horng Chau, Mohammed J Zaki, Dmitry Krotov
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Multidimensional Hopfield Networks for clustering
Gergely Stomfai, Łukasz Sienkiewicz, Barbara Rychalska
- Published: 27 Oct 2023, Last Modified: 05 Dec 2023
- AMHN23 Poster
- Readers: Everyone
Training a Hopfield Variational Autoencoder with Equilibrium Propagation
Tom Van Der Meersch, Johannes Deleu, Thomas Demeester
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Sparse Modern Hopfield Networks
Andre Martins, Vlad Niculae, Daniel C McNamee
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Skip Connections Increase the Capacity of Associative Memories in Variable Binding Mechanisms
Yi Xie, Yichen Li, Akshay Rangamani
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Long Sequence Hopfield Memory
Hamza Tahir Chaudhry, Jacob A Zavatone-Veth, Dmitry Krotov, Cengiz Pehlevan
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Oral
- Readers: Everyone
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
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
How Robust Are Energy-Based Models Trained With Equilibrium Propagation?
Siddharth Mansingh, Michal Kucer, Garrett T. Kenyon, Juston Moore, Michael Teti
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Modeling Recognition Memory with Predictive Coding and Hopfield Networks
Tianjin Li, Mufeng Tang, Rafal Bogacz
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone
Inverse distance weighting attention
Calvin McCarter
- Published: 27 Oct 2023, Last Modified: 26 Nov 2023
- AMHN23 Poster
- Readers: Everyone