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2020 – today
- 2023
[i11]Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock, Samuel L. Smith, Yee Whye Teh:
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation. CoRR abs/2302.10322 (2023)- [i10]Ryan Abbott, Michael S. Albergo, Aleksandar Botev, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, Alexander G. de G. Matthews, Sébastien Racanière, Ali Razavi, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban:
Normalizing flows for lattice gauge theory in arbitrary space-time dimension. CoRR abs/2305.02402 (2023) - 2022
- [c11]Guodong Zhang, Aleksandar Botev, James Martens:
Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers. ICLR 2022 - [i9]Guodong Zhang, Aleksandar Botev, James Martens:
Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers. CoRR abs/2203.08120 (2022) - [i8]Ryan Abbott, Michael S. Albergo, Aleksandar Botev, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Alexander G. de G. Matthews, Sébastien Racanière, Ali Razavi, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban:
Aspects of scaling and scalability for flow-based sampling of lattice QCD. CoRR abs/2211.07541 (2022) - 2021
- [c10]Aleksandar Botev, Andrew Jaegle, Peter Wirnsberger, Daniel Hennes, Irina Higgins:
Which priors matter? Benchmarking models for learning latent dynamics. NeurIPS Datasets and Benchmarks 2021 - [c9]Irina Higgins, Peter Wirnsberger, Andrew Jaegle, Aleksandar Botev:
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision. NeurIPS 2021: 25591-25605 - [i7]Aleksandar Botev, Andrew Jaegle, Peter Wirnsberger, Daniel Hennes, Irina Higgins:
Which priors matter? Benchmarking models for learning latent dynamics. CoRR abs/2111.05458 (2021) - [i6]Irina Higgins, Peter Wirnsberger, Andrew Jaegle, Aleksandar Botev:
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision. CoRR abs/2111.05986 (2021) - 2020
- [b1]Aleksandar Botev:
The Gauss-Newton matrix for Deep Learning models and its applications. University College London, UK, 2020 - [c8]Peter Toth, Danilo J. Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins:
Hamiltonian Generative Networks. ICLR 2020 - [c7]David Pfau, Irina Higgins, Aleksandar Botev, Sébastien Racanière:
Disentangling by Subspace Diffusion. NeurIPS 2020 - [i5]David Pfau, Irina Higgins, Aleksandar Botev, Sébastien Racanière:
Disentangling by Subspace Diffusion. CoRR abs/2006.12982 (2020) - [i4]James S. Spencer, David Pfau, Aleksandar Botev, W. Matthew C. Foulkes:
Better, Faster Fermionic Neural Networks. CoRR abs/2011.07125 (2020)
2010 – 2019
- 2019
- [i3]Peter Toth, Danilo Jimenez Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins:
Hamiltonian Generative Networks. CoRR abs/1909.13789 (2019) - 2018
- [c6]Hippolyt Ritter, Aleksandar Botev, David Barber:
A Scalable Laplace Approximation for Neural Networks. ICLR (Poster) 2018 - [c5]Hippolyt Ritter, Aleksandar Botev, David Barber:
Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting. NeurIPS 2018: 3742-3752 - [i2]Hippolyt Ritter, Aleksandar Botev, David Barber:
Online Structured Laplace Approximations For Overcoming Catastrophic Forgetting. CoRR abs/1805.07810 (2018) - 2017
- [c4]Aleksandar Botev, Bowen Zheng, David Barber:
Complementary Sum Sampling for Likelihood Approximation in Large Scale Classification. AISTATS 2017: 1030-1038 - [c3]Aleksandar Botev, Hippolyt Ritter, David Barber:
Practical Gauss-Newton Optimisation for Deep Learning. ICML 2017: 557-565 - [c2]Harshil Shah, David Barber, Aleksandar Botev
:
Overdispersed variational autoencoders. IJCNN 2017: 1109-1116 - [c1]Aleksandar Botev, Guy Lever, David Barber:
Nesterov's accelerated gradient and momentum as approximations to regularised update descent. IJCNN 2017: 1899-1903 - 2016
- [i1]Aleksandar Botev, Guy Lever, David Barber:
Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent. CoRR abs/1607.01981 (2016)
Coauthor Index
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last updated on 2023-05-11 21:18 CEST by the dblp team
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