The London Institute’s papers are the official record of our discoveries. They allow others to build on and apply our work. Each one is the result of many months of research, so we strive to make them clear, inspiring and beautiful, and publish them in leading journals.

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Statistical physics

Deep learning simplicity

We give a theory for the output of deep-layered machines and show that, as the network depth increases, it is biased towards simple outputs.

TFThomas Fink
ArXiv
Image for the paper "Regulatory motifs: structural and functional building blocks of genetic computation"
Combinatorics

Structure of genetic computation

The structural and functional building blocks of gene regulatory networks correspond, which tell us how genetic computation is organised.

TFThomas Fink
Submitted
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Synthetic biology

Cell soup in screens

Bursting cells can introduce noise in transcription factor screens, but modelling this process allows us to discern true counts from false.

FSForrest Sheldon
ArXiv
Image for the paper "True scale-free networks hidden by finite size effects"
Network theory

True scale-free networks

The underlying scale invariance properties of naturally occurring networks are often clouded by finite-size effects due to the sample data.

GCGuido CaldarelliM.GCAMARS.JB
Proceedings of the National Academy of Sciences of the USA
Financial risk

The price of complexity

Increasing the complexity of the network of contracts between financial institutions decreases the accuracy of estimating systemic risk.

GCSBRMTRJS
Proceedings of the National Academy of Sciences of the USA