activity
20182021
most citedAugmenting Supervised Learning by Meta-learning Unsupervised Local Rules

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG20211 cited

Augmenting Supervised Learning by Meta-learning Unsupervised Local Rules

Jeffrey Cheng, Ari Benjamin, Benjamin Lansdell +1

The brain performs unsupervised learning and (perhaps) simultaneous supervised learning. This raises the question as to whether a hybrid of supervised and unsupervised methods will…

q-bio.NC2021

A Philosophical Understanding of Representation for Neuroscience

Ben Baker, Benjamin Lansdell, Konrad Kording

Neuroscientists often describe neural activity as a representation of something, or claim to have found evidence for a neural representation. But what do these statements mean? The…

cs.LG2020

Towards intervention-centric causal reasoning in learning agents

Benjamin Lansdell

Interventions are central to causal learning and reasoning. Yet ultimately an intervention is an abstraction: an agent embedded in a physical environment (perhaps modeled as a Mark…

q-bio.NC2019

Learning to solve the credit assignment problem

Benjamin James Lansdell, Prashanth Ravi Prakash, Konrad Paul Kording

Backpropagation is driving today's artificial neural networks (ANNs). However, despite extensive research, it remains unclear if the brain implements this algorithm. Among neurosci…

stat.ML2019

Rarely-switching linear bandits: optimization of causal effects for the real world

Benjamin Lansdell, Sofia Triantafillou, Konrad Kording

Excessively changing policies in many real world scenarios is difficult, unethical, or expensive. After all, doctor guidelines, tax codes, and price lists can only be reprinted so…

q-bio.NC2018

Towards learning-to-learn

Benjamin James Lansdell, Konrad Paul Kording

In good old-fashioned artificial intelligence (GOFAI), humans specified systems that solved problems. Much of the recent progress in AI has come from replacing human insights by le…