Rob Brekelmans
Rob Brekelmans
Zweryfikowany adres z usc.edu - Strona główna
Cytowane przez
Cytowane przez
Invariant representations without adversarial training
D Moyer, S Gao, R Brekelmans, GV Steeg, A Galstyan
Advances in Neural Information Processing Systems, 2018
Auto-encoding total correlation explanation
S Gao, R Brekelmans, G Ver Steeg, A Galstyan
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
P4ML: A phased performance-based pipeline planner for automated machine learning
Y Gil, KT Yao, V Ratnakar, D Garijo, G Ver Steeg, P Szekely, ...
AutoML Workshop at ICML, 2018
Exact rate-distortion in autoencoders via echo noise
R Brekelmans, D Moyer, A Galstyan, G Ver Steeg
Advances in Neural Information Processing Systems, 3889-3900, 2019
q-Paths: Generalizing the Geometric Annealing Path using Power Means
V Masrani*, R Brekelmans*, T Bui, F Nielsen, A Galstyan, GV Steeg, ...
Uncertainty in Artificial Intelligence (UAI), 2021
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference
R Brekelmans*, V Masrani*, F Wood, GV Steeg, A Galstyan
International Conference on Machine Learning, 2020
Discovery and separation of features for invariant representation learning
A Jaiswal, R Brekelmans, D Moyer, GV Steeg, W AbdAlmageed, ...
arXiv preprint arXiv:1912.00646, 2019
Disentangled representations via synergy minimization
G Ver Steeg, R Brekelmans, H Harutyunyan, A Galstyan
2017 55th Annual Allerton Conference on Communication, Control, and …, 2017
Likelihood Ratio Exponential Families
R Brekelmans, F Nielsen, A Makhzani, A Galstyan, G Ver Steeg
NeurIPS Workshop on Deep Learning through Information Geometry, 2020
Your Policy Regularizer is Secretly an Adversary
R Brekelmans, T Genewein, J Grau-Moya, G Delétang, M Kunesch, ...
Transactions on Machine Learning Research (TMLR), 2022
Gaussian process bandit optimization of the thermodynamic variational objective
V Nguyen, V Masrani, R Brekelmans, M Osborne, F Wood
Advances in Neural Information Processing Systems 33, 5764-5775, 2020
Model-Free Risk-Sensitive Reinforcement Learning
G Delétang, J Grau-Moya, M Kunesch, T Genewein, R Brekelmans, ...
arXiv preprint arXiv:2111.02907, 2021
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
R Brekelmans, S Huang, M Ghassemi, G Ver Steeg, RB Grosse, ...
International Conference on Learning Representations (ICLR), 2021
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