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Number of items: 31.
Article
Aitchison, L;
Jegminat, J;
Menendez, JA;
Pfister, J-P;
Pouget, A;
Latham, PE;
(2021)
Synaptic plasticity as Bayesian inference.
Nature Neuroscience
, 24
pp. 565-571.
10.1038/s41593-021-00809-5.
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Beiran, M;
Dubreuil, AM;
Valente, A;
Mastrogiuseppe, F;
Ostojic, S;
(2021)
Shaping Dynamics With Multiple Populations in Low-Rank Recurrent Networks.
Neural Computation
, 33
(6)
pp. 1572-1615.
10.1162/neco_a_01381.
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Duncker, L;
Sahani, M;
(2021)
Dynamics on the manifold: Identifying computational dynamical activity from neural population recordings.
Current Opinion in Neurobiology
, 70
pp. 163-170.
10.1016/j.conb.2021.10.014.
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Fernandez, T;
Gretton, A;
Rindt, D;
Sejdinovic, D;
(2021)
A Kernel Log-Rank Test of Independence for Right-Censored Data.
Journal of the American Statistical Association
10.1080/01621459.2021.1961784.
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Fernández, T;
Rivera, N;
(2021)
A reproducing kernel Hilbert space log-rank test for the two-sample problem.
Scandinavian Journal of Statistics: Theory and Applications
, 48
(4)
pp. 1384-1432.
10.1111/sjos.12496.
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Gothner, T;
Gonçalves, PJ;
Sahani, M;
Linden, JF;
Hildebrandt, KJ;
(2021)
Sustained Activation of PV+ Interneurons in Core Auditory Cortex Enables Robust Divisive Gain Control for Complex and Naturalistic Stimuli.
Cerebral Cortex
, 31
(5)
pp. 2364-2381.
10.1093/cercor/bhaa347.
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Meunier, Dimitri;
Alquier, Pierre;
(2021)
Meta-Strategy for Learning Tuning Parameters with Guarantees.
Entropy
, 23
(10)
, Article 1257. 10.3390/e23101257.
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Poort, J;
Wilmes, KA;
Blot, A;
Chadwick, A;
Sahani, M;
Clopath, C;
Mrsic-Flogel, TD;
... Khan, AG; + view all
(2021)
Learning and attention increase visual response selectivity through distinct mechanisms.
Neuron
10.1016/j.neuron.2021.11.016.
(In press).
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Susman, L;
Mastrogiuseppe, F;
Brenner, N;
Barak, O;
(2021)
Quality of internal representation shapes learning performance in feedback neural networks.
Physical Review Research
, 3
, Article 013176. 10.1103/PhysRevResearch.3.013176.
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Trautmann, EM;
O'Shea, DJ;
Sun, X;
Marshel, JH;
Crow, A;
Hsueh, B;
Vesuna, S;
... Shenoy, KV; + view all
(2021)
Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface.
Nature Communications
, 12
(1)
, Article 3689. 10.1038/s41467-021-23884-5.
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Proceedings paper
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Amjad, Jaweria;
Lyu, Zhaoyan;
Rodrigues, Miguel RD;
(2021)
Regression with Deep Neural Networks: Generalization Error Guarantees, Learning Algorithms, and Regularizers.
In:
2021 29th European Signal Processing Conference (EUSIPCO).
(pp. pp. 1481-1485).
IEEE: Dublin, Ireland.
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Arbel, M;
Zhou, L;
Gretton, A;
(2021)
Generalized Energy Based Models.
In:
Proceedings of the 9th International Conference on Learning Representations: ICLR 2021.
ICLR
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Duncker, L;
Driscoll, L;
Shenoy, K;
Sahani, M;
Susillo, D;
(2021)
Organizing recurrent network dynamics by task-computation to enable continual learning.
In:
Advances in Neural Information Processing Systems 33.
NeurIPS
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Glaser, P;
Arbel, M;
Gretton, A;
(2021)
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support.
In: Ranzato, M and Beygelzimer, A and Dauphin, Y and Liang, PS and Wortman Vaughan, J, (eds.)
Advances in Neural Information Processing Systems 34 (NeurIPS 2021).
(pp. pp. 8018-8031).
NeurIPS
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Juechems, K;
Saxe, A;
(2021)
Inferring Actions, Intentions, and Causal Relations in a Deep Neural Network.
In:
Proceedings of the 43rd Annual Meeting of the Cognitive Science Society.
(pp. pp. 1056-1062).
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Lee, S;
Goldt, S;
Saxe, A;
(2021)
Continual Learning in the Teacher-Student Setup: Impact of Task Similarity.
In: Meila, M and Zhang, T, (eds.)
Proceedings of the 38th International Conference on Machine Learning.
(pp. pp. 6109-6119).
MLResearch Press
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Li, Y;
Pogodin, R;
Sutherland, DJ;
Gretton, A;
(2021)
Self-Supervised Learning with Kernel Dependence Maximization.
In:
Advances in Neural Information Processing Systems 34 (NeurIPS 2021).
(pp. pp. 15543-15556).
NeurIPS
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Marx, A;
Gretton, A;
Mooij, JM;
(2021)
A Weaker Faithfulness Assumption based on Triple Interactions.
In:
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence.
(pp. pp. 451-460).
Proceedings of Machine Learning Research: Online conference.
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Mastouri, Afsaneh;
Zhu, Yuchen;
Gultchin, Limor;
Korba, Anna;
Silva, Ricardo;
Kusner, Matt J;
Gretton, Arthur;
(2021)
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction.
In: Meila, M and Zhang, T, (eds.)
Proceedings of the 38 th International Conference on Machine Learning.
(pp. pp. 1-12).
PMLR
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Moskovitz, T;
Arbel, M;
Huszar, F;
Gretton, A;
(2021)
EFFICIENT WASSERSTEIN NATURAL GRADIENTS FOR REINFORCEMENT LEARNING.
In:
Proceedings of the 9th International Conference on Learning Representations: ICLR 2021.
ICLR: Virtual conference.
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Moskovitz, Ted;
Arbel, Michael;
Huszar, Ferenc;
Gretton, Arthur;
(2021)
Efficient Wasserstein Natural Gradients for Reinforcement Learning.
In:
ICLR 2021 - 9th International Conference on Learning Representations.
ICLR
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Pogodin, R;
Mehta, Y;
Lillicrap, TP;
Latham, PE;
(2021)
Towards Biologically Plausible Convolutional Networks.
In:
Advances in Neural Information Processing Systems 34 pre-proceedings (NeurIPS 2021).
NeurIPs
(In press).
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Sarao Mannelli, Stefano;
Urbani, Pierfrancesco;
(2021)
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems.
In:
NeurIPS Proceedings.
NeurIPS
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Saxe, Andrew;
Juechems, Keno;
(2021)
Inferring Actions, Intentions, and Causal Relations in a Deep Neural Network.
In:
Proceedings of the Annual Meeting of the Cognitive Science Society.
(pp. pp. 1056-1062).
Cognitive Science Society: Philadelphia USA.
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Schwarz, J;
Jayakumar, SM;
Pascanu, R;
Latham, PE;
Teh, YW;
(2021)
Powerpropagation: A sparsity inducing weight reparameterisation.
In:
Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems.
NeurIPS
(In press).
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Soulat, H;
Keshavarzi, S;
Margrie, TW;
Sahani, M;
(2021)
Probabilistic Tensor Decomposition of Neural Population Spiking Activity.
In: Ranzato, M and Beygelzimer, A and Dauphin, Y and Liang, PS and Wortman Vaughan, J, (eds.)
Advances in Neural Information Processing Systems 34 (NeurIPS 2021).
(pp. pp. 15969-15980).
NeurIPS
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Xu, L;
Chen, Y;
Srinivasan, S;
de Freitas, N;
Doucet, A;
Gretton, A;
(2021)
Learning Deep Features in Instrumental Variable Regression.
In:
Proceedings of the 9th International Conference on Learning Representations: ICLR 2021.
ICLR
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Thesis
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Ahilan, Sanjeevan;
(2021)
Structures for Sophisticated Behaviour: Feudal Hierarchies and World Models.
Doctoral thesis (Ph.D), UCL (University College London).
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Duncker, Lea;
(2021)
Dynamical structure in neural population activity.
Doctoral thesis (Ph.D), UCL (University College London).
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Xu, Wenkai;
(2021)
Advances in Non-parametric Hypothesis Testing with Kernels.
Doctoral thesis (Ph.D), UCL (University College London).
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Zamfir, Elena;
(2021)
Investigating the complexity of interactions between attributions and beliefs: evidence from a novel task.
Doctoral thesis (Ph.D), UCL (University College London).
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