Aitchison, Laurence - Citegraph

Author Info

Name	Affiliation	Papers
AITCHISON, LAURENCE	UCL, Gatsby Computat Neurosci Unit, London, England	19
Collaborators	Citations	PageRank
30	20	7.00
Referers	Referees	References
74	128	47

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100128

Publications (19 rows)

Collaborators (30 rows)

Referers (74 rows)

Referees (100 rows)

Title	Citations	PageRank	Year
Data augmentation in Bayesian neural networks and the cold posterior effect.	0	0.34	2022
Bayesian Neural Network Priors Revisited	0	0.34	2022
A statistical theory of cold posteriors in deep neural networks	0	0.34	2021
Gradient Regularization as Approximate Variational Inference	0	0.34	2021
: A library for Bayesian neural network inference with different prior distributions.	0	0.34	2021
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes	0	0.34	2021
Deep Kernel Processes	0	0.34	2021
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods	0	0.34	2020
Why bigger is not always better: on finite and infinite neural networks	0	0.34	2020
Deep Convolutional Networks as shallow Gaussian Processes	5	0.40	2019
Deep Convolutional Networks as shallow Gaussian Processes.	8	0.49	2018
A unified theory of adaptive stochastic gradient descent as Bayesian filtering.	1	0.37	2018
Discrete flow posteriors for variational inference in discrete dynamical systems.	0	0.34	2018
Tensor Monte Carlo: Particle Methods for the GPU era	0	0.34	2018
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit.	1	0.37	2017
Zipf's Law Arises Naturally When There Are Underlying, Unobserved Variables.	0	0.34	2016
The Hamiltonian Brain: Efficient Probabilistic Inference with Excitatory-Inhibitory Neural Circuit Dynamics.	1	0.35	2016
Doubly Bayesian Analysis Of Confidence In Perceptual Decision-Making	2	0.54	2015
Fast Sampling-Based Inference in Balanced Neuronal Networks.	2	0.43	2014

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