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Number of items: 20.
A
Arbel, M;
Gretton, AL;
(2018)
Kernel Conditional Exponential Family.
In:
Proceedings of the 21st International Conference on Artifi- cial Intelligence and Statistics (AISTATS) 2018.
(pp. pp. 1337-1346).
PMLR
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Arbel, M;
Sutherland, DJ;
Bińkowski, M;
Gretton, A;
(2018)
On gradient regularizers for MMD GANs.
In: Bengio, S and Wallach, H and Larochelle, H and Grauman, K and Cesa-Bianchi, N and Garnett, R, (eds.)
Advances in Neural Information Processing Systems 31 (NIPS 2018).
NIPS Proceedings: Montreal, Canada.
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Asabuki, T;
Hiratani, N;
Fukai, T;
(2018)
Interactive reservoir computing for chunking information streams.
PLoS Computational Biology
, 14
(10)
, Article e1006400. 10.1371/journal.pcbi.1006400.
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B
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Bińkowski, M;
Sutherland, DJ;
Arbel, M;
Gretton, A;
(2018)
Demystifying MMD GANs.
In: Bengio, Yoshua and LeCun, Yann, (eds.)
Proceedings of ICLR 2018 : International Conference on Learning Representations.
ICLR: Vancouver, BC, Canada,.
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Bröker, F;
Marshall, L;
Bestmann, S;
Dayan, P;
(2018)
Forget-me-some: General versus special purpose models in a hierarchical probabilistic task.
PLoS One
, 13
(10)
, Article e0205974. 10.1371/journal.pone.0205974.
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D
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Duncker, L;
Sahani, M;
(2018)
Temporal alignment and latent Gaussian process factor inference in population spike trains.
In: Bengio, S and Wallach, H and Larochelle, H and Grauman, K and CesaBianchi, N and Garnett, R, (eds.)
Proceedings of Conference on Neural Information Processing Systems 31 (NIPS 2018).
Neural Information Processing Systems (NIPS): Montreal, Canada.
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H
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Hehrmann, Phillipp;
(2018)
Pitch perception as probabilistic inference.
Doctoral thesis (Ph.D), UCL (University College London).
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Higgins, I;
Sonnerat, N;
Matthey, L;
Pal, A;
Burgess, CP;
Bošnjak, M;
Shanahan, M;
... Lerchner, A; + view all
(2018)
SCAN: Learning Hierarchical Compositional Visual Concepts.
In: Bengio, Y and LeCun, Y, (eds.)
Proceedings of the Sixth International Conference on Learning Representations (ICLR 2018).
International Conference on Learning Representations (ICLR): Vancouver, Canada.
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Hiratani, N;
Fukai, T;
(2018)
Redundancy in synaptic connections enables neurons to learn optimally.
Proceedings of the National Academy of Sciences
, 115
(29)
E6871-E6879.
10.1073/pnas.1803274115.
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J
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Jitkrittum, W;
Sangkloy, P;
Schölkopf, B;
Kanagawa, H;
Hays, J;
Gretton, A;
(2018)
Informative features for model comparison.
In:
Advances in Neural Information Processing Systems 31 (NIPS 2018).
(pp. pp. 808-819).
Neural Information Processing Systems Foundation, Inc.: Montréal, Canada.
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K
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Khan, AG;
Poort, J;
Chadwick, A;
Blot, A;
Sahani, M;
Mrsic-Flogel, TD;
Hofer, SB;
(2018)
Distinct learning-induced changes in stimulus selectivity and interactions of GABAergic interneuron classes in visual cortex.
Nature Neuroscience
, 21
(6)
pp. 851-859.
10.1038/s41593-018-0143-z.
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Korshunova, I;
Degrave, J;
Huszár, F;
Gal, Y;
Gretton, A;
Dambre, J;
(2018)
Bruno: A deep recurrent model for exchangeable data.
In:
Advances in Neural Information Processing Systems 31 (NIPS 2018).
(pp. pp. 7190-7198).
Neural Information Processing Systems Foundation, Inc.: Montréal, Canada.
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L
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Lorenz, R;
Violante, IR;
Monti, RP;
Montana, G;
Hampshire, A;
Leech, R;
(2018)
Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization.
Nature Communications
, 9
(1)
, Article 1227. 10.1038/s41467-018-03657-3.
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M
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Meyer, AF;
Poort, J;
O'Keefe, J;
Sahani, M;
Linden, JF;
(2018)
A Head-Mounted Camera System Integrates Detailed Behavioral Monitoring with Multichannel Electrophysiology in Freely Moving Mice.
Neuron
, 100
(1)
pp. 46-60.
10.1016/j.neuron.2018.09.020.
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Monti, RP;
Anagnostopoulos, C;
Montana, G;
(2018)
Adaptive regularization for Lasso models in the context of non-stationary data streams.
Statistical Analysis and Data Mining
, 11
(5)
, Article 11390. 10.1002/sam.11390.
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Monti, RP;
Hyvärinen, A;
(2018)
A Unified Probabilistic Model for Learning Latent Factors and Their Connectivities from High-Dimensional Data.
In:
Proceedings of Conference on Uncertainty in Artificial Intelligence - UAI 2018.
Uncertainty in Artificial Intelligence (UAI): USA.
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Monti, RP;
Tootoonian, S;
Cao, R;
(2018)
Avoiding degradation in deep feed-forward networks by phasing out skip-connections.
In:
Proceedings of the International Conference on Artificial Neural Networks and Machine Learning : ICANN 2018.
(pp. pp. 447-456).
Springer: Rhodes, Greece.
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S
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Soldado Magraner, Joana;
(2018)
Linear Dynamics of Evidence Integration in Contextual Decision Making.
Doctoral thesis (Ph.D), UCL (University College London).
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Strathmann, Heiko;
(2018)
Kernel methods for Monte Carlo.
Doctoral thesis (Ph.D), UCL (University College London).
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V
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Vertes, E;
Sahani, M;
(2018)
Flexible and accurate inference and learning for deep generative models.
In:
Proceedings of 32nd Conference on Neural Information Processing Systems (NeurIPS 2018),.
Neural Information Processing Systems (NIPS): Montréal, Canada..
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