Следене
Katie Everett
Katie Everett
Google DeepMind, MIT
Потвърден имейл адрес: google.com
Заглавие
Позовавания
Позовавания
Година
Disentanglement via mechanism sparsity regularization: A new principle for nonlinear ICA
S Lachapelle, P Rodriguez, Y Sharma, KE Everett, R Le Priol, A Lacoste, ...
Conference on Causal Learning and Reasoning, 428-484, 2022
1432022
GFlowNets and variational inference
N Malkin, S Lahlou, T Deleu, X Ji, E Hu, K Everett, D Zhang, Y Bengio
arXiv preprint arXiv:2210.00580, 2022
832022
Small-scale proxies for large-scale transformer training instabilities
M Wortsman, PJ Liu, L Xiao, K Everett, A Alemi, B Adlam, JD Co-Reyes, ...
arXiv preprint arXiv:2309.14322, 2023
732023
GFlowNet-EM for learning compositional latent variable models
EJ Hu, N Malkin, M Jain, KE Everett, A Graikos, Y Bengio
International Conference on Machine Learning, 13528-13549, 2023
452023
Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description
A Kumok, A Fabrikant, AM Dai, C Kamath, C Stanton, D Desfontaines, ...
Technical Report. N/A. URL: https://arxiv. org/abs, 2020
24*2020
Nonparametric partial disentanglement via mechanism sparsity: Sparse actions, interventions and sparse temporal dependencies
S Lachapelle, PR López, Y Sharma, K Everett, RL Priol, A Lacoste, ...
arXiv preprint arXiv:2401.04890, 2024
202024
Scaling exponents across parameterizations and optimizers
K Everett, L Xiao, M Wortsman, AA Alemi, R Novak, PJ Liu, I Gur, ...
arXiv preprint arXiv:2407.05872, 2024
192024
Nanodo: A minimal transformer decoder-only language model implementation in JAX., 2024
PJ Liu, R Novak, J Lee, M Wortsman, L Xiao, K Everett, AA Alemi, ...
URL http://github. com/google-deepmind/nanodo, 0
7
Cycles in Causal Learning
K Everett, I Fischer
ICLR Workshop on Causal Learning for Decision Making, 2020
2020
Системата не може да изпълни операцията сега. Опитайте отново по-късно.
Статии 1–9