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Number of items: 17.
Article
Fernández, T;
Rivera, N;
(2020)
Kaplan-Meier V- and U-statistics.
Electronic Journal of Statistics
, 14
(1)
pp. 1872-1916.
10.1214/20-ejs1704.
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Hiratani, N;
Latham, PE;
(2020)
Rapid Bayesian learning in the mammalian olfactory system.
Nature Communications
, 11
(1)
, Article 3845. 10.1038/s41467-020-17490-0.
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Jerjian, SJ;
Sahani, M;
Kraskov, A;
(2020)
Movement initiation and grasp representation in premotor and primary motor cortex mirror neurons.
eLife
, 9
, Article e54139. 10.7554/eLife.54139.
(In press).
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Korshunova, I;
Gal, Y;
Gretton, A;
Dambre, J;
(2020)
Conditional BRUNO: A neural process for exchangeable labelled data.
Neurocomputing
, 416
pp. 305-309.
10.1016/j.neucom.2019.11.108.
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Najafi, F;
Elsayed, GF;
Cao, R;
Pnevmatikakis, E;
Latham, PE;
Cunningham, JP;
Churchland, AK;
(2020)
Excitatory and Inhibitory Subnetworks Are Equally Selective during Decision-Making and Emerge Simultaneously during Learning.
Neuron
, 105
(1)
165-179.e8.
10.1016/j.neuron.2019.09.045.
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Rusakov, DA;
Savtchenko, LP;
Latham, PE;
(2020)
Noisy Synaptic Conductance: Bug or a Feature?
Trends in Neurosciences
, 43
(6)
pp. 363-372.
10.1016/j.tins.2020.03.009.
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Proceedings paper
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Fernández, T;
Xu, W;
Ditzhaus, M;
Gretton, A;
(2020)
A kernel test for quasi-independence.
In: Larochelle, H. and Ranzato, M. and Hadsell, R. and Balcan, M.F. and Lin, H., (eds.)
NIPS'20: Proceedings of the 34th International Conference on Neural Information Processing Systems.
Neural Information Processing Systems Conference: Vancouver, Canada.
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Fernandez Aguilar, T;
Gretton, A;
Rivera, N;
XU, W;
(2020)
Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data.
In:
Proceedings of the 37th International Conference on Machine Learning.
(pp. pp. 3112-3122).
PMLR: Vienna, Austria.
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Korba, A;
Salim, A;
Arbel, M;
Luise, G;
Gretton, A;
(2020)
A Non-Asymptotic Analysis for
Stein Variational Gradient Descent.
In: Larochelle, H. and Ranzato, M. and Hadsell, R. and Balcan, M.F. and Lin, H., (eds.)
NIPS'20: Proceedings of the 34th International Conference on Neural Information Processing Systems.
Neural Information Processing Systems Conference: Vancouver, Canada.
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Liu, F;
Xu, W;
Lu, J;
Zhang, G;
Gretton, A;
Sutherland, DJ;
(2020)
Learning deep kernels for non-parametric two-sample tests.
In:
Proceedings of the 37th International Conference on Machine Learning.
(pp. pp. 6272-6282).
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Pogodin, R;
Latham, PE;
(2020)
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks.
In:
Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS 2020).
NeurIPS: Vancouver, Canada.
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Rutten, V;
Bernacchia, A;
Sahani, M;
Hennequin, G;
(2020)
Non-reversible Gaussian processes for identifying latent dynamical structure in neural data.
In:
Advances in Neural Information Processing Systems 33 (NeurIPS 2020).
NeurIPS
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Sarao Mannelli, Stefano;
Biroli, Giulio;
Cammarota, Chiara;
Krzakala, Florent;
Urbani, Pierfrancesco;
Zdeborova, Lenka;
(2020)
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval.
In:
NeurIPS Proceedings.
NeurIPS
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Sarao Mannelli, Stefano;
Vanden-Eijnden, Eric;
Zdeborova, Lenka;
(2020)
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions.
In:
NeurIPS Proceedings.
NeurIPS
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Wenliang, LK;
Moskovitz, T;
Kanagawa, H;
Sahani, M;
(2020)
Amortised learning by wake-sleep.
In:
Proceedings of the 37th International Conference on Machine Learning,.
(pp. pp. 10167-10178).
PMLR: Proceedings of Machine Learning Research
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Working / discussion paper
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Lin, I-Chun;
Okun, Michael;
Carandini, Matteo;
Harris, Kenneth D;
(2020)
Equations governing dynamics of excitation and inhibition in the mouse corticothalamic network.
BioRxiv: Cold Spring Harbor, NY, USA.
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Thesis
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Jativa Vega, Sofia Alejandra;
(2020)
A second look at memory: Different Approaches to Understanding Diversity in Memory and Cognition.
Doctoral thesis (Ph.D), UCL (University College London).
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