Browse by UCL Departments and Centres
Group by: Author | Type
Number of items: 26.
A
Alabdulmohsin, Ibrahim;
Chiou, Nicole;
D’Amour, Alexander;
Gretton, Arthur;
Koyejo, Sanmi;
Kusner, Matt J;
Pfohl, Stephen R;
... Tsai, Katherine; + view all
(2023)
Adapting to Latent Subgroup Shifts via Concepts and Proxies.
In:
Proceedings of The 26th International Conference on Artificial Intelligence and Statistics.
(pp. pp. 9637-9661).
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B
Baume, Jerome;
Kanagawa, Heishiro;
Gretton, Arthur;
(2023)
A Kernel Stein Test of Goodness of Fit for Sequential Models.
In:
Proceedings of the International Conference on Machine Learning.
ICML Proceedings
(In press).
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D
Dorrell, Will;
Latham, Peter;
Behrens, Timothy EJ;
Whittington, James CR;
(2023)
Actionable Neural Representations: Grid Cells from Minimal Constraints.
In:
Proceedings of the Eleventh International Conference on Learning Representations.
(pp. pp. 1-47).
ICLR
(In press).
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Dorrell, William;
Yuffa, Maria;
Latham, Peter;
(2023)
Meta-Learning the Inductive Bias of Simple Neural Circuits.
In:
Proceedings of the International Conference on Machine Learning.
ICML Proceedings
(In press).
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F
Flesch, T;
Nagy, DG;
Saxe, A;
Summerfield, C;
(2023)
Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signals.
PLoS Computational Biology
, 19
(1)
, Article e1010808. 10.1371/journal.pcbi.1010808.
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Flesch, Timo;
Saxe, Andrew;
Summerfield, Christopher;
(2023)
Continual task learning in natural and artificial agents.
Trends in Neurosciences
10.1016/j.tins.2022.12.006.
(In press).
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G
Galgali, AR;
Sahani, M;
Mante, V;
(2023)
Residual dynamics resolves recurrent contributions to neural computation.
Nature Neuroscience
, 26
pp. 326-338.
10.1038/s41593-022-01230-2.
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H
Hiratani, naoki;
Mehta, Yash;
Lillicrap, Timothy;
Latham, Peter;
(2023)
On the Stability and Scalability of Node Perturbation Learning.
In:
Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS 2022).
Neural Information Processing Systems (NeurIPS)
(In press).
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Huang, Han;
Liu, Xing;
Duncan, Andrew B;
Gandy, Axel;
(2023)
A High-dimensional Convergence Theorem for U-statistics
with Applications to Kernel-based Testing.
In:
Causal Inference Reading Group.
University of Cambridge: Cambridge, UK.
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I
International Brain Laboratory;
Bonacchi, Niccolò;
Chapuis, Gaelle A;
Churchland, Anne K;
DeWitt, Eric EJ;
Faulkner, Mayo;
Harris, Kenneth D;
... Wells, Miles J; + view all
(2023)
A modular architecture for organizing, processing and sharing neurophysiology data.
Nature Methods
, 20
pp. 403-407.
10.1038/s41592-022-01742-6.
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J
Jarvis, Devon;
Klein, Richard;
Rosman, Benjamin;
Saxe, Andrew;
(2023)
On The Specialization of Neural Modules.
In:
Proceedings of the Eleventh International Conference on Learning Representations.
(pp. pp. 1-31).
ICLR
(In press).
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K
Kanagawa, Heishiro;
Jitkrittum, Wittawat;
Mackey, Lester;
Fukumizu, Kenji;
Gretton, Arthur;
(2023)
A kernel Stein test for comparing latent variable models.
Journal of the Royal Statistical Society: Statistical Methodology Series B
, Article qkad050. 10.1093/jrsssb/qkad050.
(In press).
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M
Masís, J;
Chapman, T;
Rhee, JY;
Cox, DD;
Saxe, AM;
(2023)
Strategically managing learning during perceptual decision making.
eLife
, 12
, Article e64978. 10.7554/eLife.64978.
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Mastrogiuseppe, Francesca;
Hiratani, Naoki;
Latham, Peter;
(2023)
Evolution of neural activity in circuits bridging sensory and abstract knowledge.
eLife
, 12
, Article e79908. 10.7554/eLife.79908.
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Moskovitz, Theodore;
O'Donoghue, Brendan;
Veeriah, Vivek;
Flennerhag, Sebastian;
Singh, Satinder;
Zahavy, Tom;
(2023)
ReLOAD: reinforcement learning with optimistic ascent-descent for last-iterate convergence in constrained MDPs.
In:
Proceedings of the 40 th International Conference on Machine Learning.
(pp. pp. 25303-25336).
PMLR 202: Honolulu, Hawaii, USA.
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N
Nelli, Stephanie;
Braun, Lukas;
Dumbalska, Tsvetomira;
Saxe, Andrew;
Summerfield, Christopher;
(2023)
Neural knowledge assembly in humans and neural networks.
Neuron
10.1016/j.neuron.2023.02.014.
(In press).
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P
Pogodin, Roman;
(2023)
Deep Learning Models of Learning in the Brain.
Doctoral thesis (Ph.D), UCL (University College London).
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Pogodin, Roman;
Deka, Namrata;
Li, Yazhe;
Sutherland, Danica J;
Veitch, Victor;
Gretton, Arthur;
(2023)
Efficient Conditionally Invariant Representation Learning.
In:
Proceedings of the Eleventh International Conference on Learning Representations.
(pp. p. 4723).
International Conference on Learning Representations: Kigali, Rwanda.
(In press).
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S
Schrab, Antonin;
Guedj, Benjamin;
Gretton, Arthur;
(2023)
KSD Aggregated Goodness-of-fit Test.
In:
Proceedings of the Advances in Neural Information Processing Systems 35 (NeurIPS 2022).
NeurIPS
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Schrab, Antonin;
Kim, Ilmun;
Albert, Mélisande;
Laurent, Béatrice;
Guedj, Benjamin;
Gretton, Arthur;
(2023)
MMD Aggregated Two-Sample Test.
Journal of Machine Learning Research (JMLR)
, 24
, Article 194.
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Shamash, Philip;
Lee, Sebastian;
Saxe, Andrew M;
Branco, Tiago;
(2023)
Mice identify subgoal locations through an action-driven mapping process.
Neuron
10.1016/j.neuron.2023.03.034.
(In press).
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Singh, Aaditya K;
Ding, David;
Saxe, Andrew;
Hill, Felix;
Lampinen, Andrew Kyle;
(2023)
Know your audience: specializing grounded language models with listener subtraction.
In:
EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference.
(pp. pp. 3884-3911).
Association for Computational Linguistics: Dubrovnik, Croatia.
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Sun, Weinan;
Advani, Madhu;
Spruston, Nelson;
Saxe, Andrew;
Fitzgerald, James E;
(2023)
Organizing memories for generalization in complementary learning systems.
Nature Neuroscience
10.1038/s41593-023-01382-9.
(In press).
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W
Walker, william;
Soulat, hugo;
Yu, changmin;
Sahani, Maneesh;
(2023)
Unsupervised representation learning with recognition-parametrised probabilistic models.
In:
Proceedings of the 26th International Conference on Artificial Intelligence and Statistics.
Proceedings of Machine Learning Research: Valencia, Spain Proceedings of Machine Learning Research.
(In press).
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X
Xu, Liyuan;
Gretton, Arthur;
(2023)
A Neural Mean Embedding Approach for Back-door and Front-door Adjustment.
In:
Proceedings of the Eleventh International Conference on Learning Representations.
(pp. p. 2756).
International Conference on Learning Representations: Kigali, Rwanda.
(In press).
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Z
Zhou, Liang;
Smith, Kevin A;
Tenenbaum, Joshua B;
Gerstenberg, Tobias;
(2023)
Mental jenga: A counterfactual simulation model of causal judgments about physical support.
Journal of Experimental Psychology: General
10.1037/xge0001392.
(In press).
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