25 citations · 62 across the 12 of their papers we have counts for
12 papers
Associative memory inspires improvements for in-context learning using a novel attention residual stream architecture
Thomas F Burns, Tomoki Fukai, Christopher J Earls
Large language models (LLMs) demonstrate an impressive ability to utilise information within the context of their input sequences to appropriately respond to data unseen by the LLM…
convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data
Roman Koshkin, Tomoki Fukai
Spontaneous neural activity, crucial in memory, learning, and spatial navigation, often manifests itself as repetitive spatiotemporal patterns. Despite their importance, analyzing…
An Inherent Trade-Off in Noisy Neural Communication with Rank-Order Coding
Ibrahim Alsolami, Tomoki Fukai
Rank-order coding, a form of temporal coding, has emerged as a promising scheme to explain the rapid ability of the mammalian brain. Owing to its speed as well as efficiency, rank-…
Simplicial Hopfield networks
Thomas F Burns, Tomoki Fukai
Hopfield networks are artificial neural networks which store memory patterns on the states of their neurons by choosing recurrent connection weights and update rules such that the…
Goal-oriented inference of environment from redundant observations
Kazuki Takahashi, Tomoki Fukai, Yutaka Sakai +1
The agent learns to organize decision behavior to achieve a behavioral goal, such as reward maximization, and reinforcement learning is often used for this optimization. Learning a…
An Extension of Fisher's Criterion: Theoretical Results with a Neural Network Realization
Ibrahim Alsolami, Tomoki Fukai
Fisher's criterion is a widely used tool in machine learning for feature selection. For large search spaces, Fisher's criterion can provide a scalable solution to select features.…