Browse by UCL Departments and Centres
![[up]](/style/images/multi_up.png)
Up a levelGroup by: Author | Type
Number of items: 20.
B
|
Biderman, Dan;
Whiteway, Matthew R;
Hurwitz, Cole;
Greenspan, Nicholas;
Lee, Robert S;
Vishnubhotla, Ankit;
Warren, Richard;
... Paninski, Liam; + view all
(2024)
Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling and cloud-native open-source tools.
Nature Methods
, 21
(7)
pp. 1316-1328.
10.1038/s41592-024-02319-1.
|
Borges, Beatriz;
Foroutan, Negar;
Bayazit, Deniz;
Sotnikova, Anna;
Montariol, Syrielle;
Nazaretzky, Tanya;
Banaei, Mohammadreza;
... Bosselut, Antoine; + view all
(2024)
Could ChatGPT get an engineering degree? Evaluating higher education vulnerability to AI assistants.
Proceedings of the National Academy of Sciences
, 121
(49)
, Article e2414955121. 10.1073/pnas.2414955121.
|
G
|
Galashov, A;
Titsias, MK;
György, A;
Lyle, C;
Pascanu, R;
Teh, YW;
Sahani, M;
(2024)
Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset.
In:
Proceedings of the Advances in Neural Information Processing Systems 37 (NeurIPS 2024).
NeurIPS
|
 |
|
Glaser, Pierre;
Huang, Kevin Han;
Gretton, Arthur;
(2024)
Near-Optimality of Contrastive Divergence Algorithms.
In: Globerson, A and Mackey, L and Belgrave, D and Fan, A and Paquet, U and Tomczak, J and Zhang, C, (eds.)
Advances in Neural Information Processing Systems 37 (NeurIPS 2024).
(pp. pp. 1-55).
NeurIPS: Vancouver, BC, Canada.
|
|
H
|
Hromadka, Samo;
Sahani, Maneesh;
(2024)
Modelling Latent Dynamical Systems with Recognition-Parametrised Models.
In:
Proceedings of the Workshop: Structured Probabilistic Inference and Generative Modeling.
ICML
(In press).
|
|
J
|
Jo (Xu), Ritsugen (Liyuan);
(2024)
Feature Mean Embeddings for Causal Inference.
Doctoral thesis (Ph.D), UCL (University College London).
|
K
|
Kunin, Daniel;
Raventos, Allan;
Domine, Clementine;
Chen, Feng;
Klindt, David;
Saxe, Andrew;
Ganguli, Surya;
(2024)
Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning.
In:
Advances in Neural Information Processing Systems 37 (NeurIPS 2024).
NeurIPS Proceedings
|
 |
L
|
Li, Zhu;
Meunier, Dimitri;
Mollenhauer, Mattes;
Gretton, Arthur;
(2024)
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm.
Journal of Machine Learning Research (JMLR)
, 25
(181)
pp. 1-51.
|
|
|
Löwe, Anika T;
Touzo, Léo;
Muhle-Karbe, Paul S;
Saxe, Andrew M;
Summerfield, Christopher;
Schuck, Nicolas W;
(2024)
Abrupt and spontaneous strategy switches emerge in simple regularised neural networks.
PLoS Computational Biology
, 20
(10)
, Article e1012505. 10.1371/journal.pcbi.1012505.
|
M
|
Meunier, Dimitri;
Shen, Zikai;
Mollenhauer, Mattes;
Gretton, Arthur;
Li, Zhu;
(2024)
Optimal Rates for Vector-Valued Spectral
Regularization Learning Algorithms.
In: Globerson, A and Mackey, L and Belgrave, D and Fan, A and Paquet, U and Tomczak, J and Zhang, C, (eds.)
Advances in Neural Information Processing Systems 37 (NeurIPS 2024).
(pp. pp. 1-46).
NeurIPS: Vancouver, BC, Canada.
|
|
P
|
Pegoraro, Marco;
Domine, Clementine;
Rodola, Emanuele;
Velickovic, Petar;
Deac, Andreea;
(2024)
Geometric epitope and paratope prediction.
Bioinformatics
, 40
(7)
, Article btae405. 10.1093/bioinformatics/btae405.
|
|
R
|
Ruetten, Virginia Marie Sophie;
(2024)
Whole body-brain functional imaging and interrogation platform: technology development, analysis methods and applications.
Doctoral thesis (Ph.D), UCL (University College London).
|
S
|
Sandbrink, Kai;
Bauer, Jan;
Proca, Alexandra M;
Saxe, Andrew;
Summerfield, Christopher;
Hummos, Ali;
(2024)
Flexible task abstractions emerge in linear networks with fast and bounded units.
In:
Advances in Neural Information Processing Systems 37 (NeurIPS 2024).
NeurIPS: Vancouver, Canada.
(In press).
|
|
Sarao Mannelli, Stefano;
Ivashynka, Yaraslau;
Saxe, Andrew;
Saglietti, Luca;
(2024)
Tilting the odds at the lottery: the interplay of overparameterisation and curricula in neural networks.
Journal of Statistical Mechanics: Theory and Experiment
, 2024
(11)
, Article 114001. 10.1088/1742-5468/ad864b.
|
|
Schrouff, Jessica;
Bellot, Alexis;
Rannen-Triki, Amal;
Malek, Alan;
Albuquerque, Isabela;
Gretton, Arthur;
D'Amour, Alexander;
(2024)
Mind the Graph When Balancing Data for Fairness
or Robustness.
In: Globerson, A and Mackey, L and Belgrave, D and Fan, A and Paquet, U and Tomczak, J and Zhang, C, (eds.)
Advances in Neural Information Processing Systems 37 (NeurIPS 2024).
(pp. pp. 1-35).
NeurIPS: Vancouver, BC, Canada.
|
|
|
Sclocchi, Antonio;
Wyart, Matthieu;
(2024)
On the different regimes of stochastic gradient descent.
Proceedings of the National Academy of Sciences (PNAS)
, 121
(9)
, Article e2316301121. 10.1073/pnas.2316301121.
|
|
V
|
van Rossem, L;
Saxe, AM;
(2024)
When Representations Align: Universality in Representation Learning Dynamics.
In:
Proceedings of the 41st International Conference on Machine Learning.
(pp. pp. 49098-49121).
Proceedings of Machine Learning Research: Vienna, Austria.
|
|
W
|
Walker, William;
(2024)
Probabilistic Unsupervised Learning using Recognition Parameterized Models.
Doctoral thesis (Ph.D), UCL (University College London).
|
|
Wiltzer, H;
Farebrother, J;
Gretton, A;
Rowland, M;
(2024)
Foundations of Multivariate Distributional Reinforcement Learning.
In: Globerson, A and Mackey, L and Belgrave, D and Fan, A and Paquet, U and Tomczak, J and Zhang, C, (eds.)
Advances in Neural Information Processing Systems 37.
Neural Information Processing Systems Foundation, Inc. (NeurIPS): Vancouver, Canada.
|
|
Z
|
Zhang, Yedi;
Latham, Peter E;
Saxe, Andrew M;
(2024)
Understanding Unimodal Bias in Multimodal Deep Linear Networks.
In: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix, (eds.)
Proceedings of the 41st International Conference on Machine Learning.
(pp. pp. 59100-59125).
Proceedings of Machine Learning Research (PMLR): Vienna, Austria.
|
