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Polina Kirichenko
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Why normalizing flows fail to detect out-of-distribution data
P Kirichenko, P Izmailov, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2020
1152020
Subspace inference for bayesian deep learning
P Izmailov, WJ Maddox, P Kirichenko, T Garipov, D Vetrov, AG Wilson
Uncertainty in Artificial Intelligence (UAI), 2019
992019
Swalp: Stochastic weight averaging in low-precision training
G Yang, T Zhang, P Kirichenko, J Bai, AG Wilson, C De Sa
International Conference on Machine Learning (ICML), 2019
692019
Semi-Supervised Learning with Normalizing Flows
P Izmailov, P Kirichenko, M Finzi, AG Wilson
International Conference on Machine Learning (ICML), 2019
672019
Does Knowledge Distillation Really Work?
S Stanton, P Izmailov, P Kirichenko, AA Alemi, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2021
582021
Last layer re-training is sufficient for robustness to spurious correlations
P Kirichenko, P Izmailov, AG Wilson
International Conference on Learning Representations (ICLR 2023), 2022
322022
Invertible convolutional networks
M Finzi, P Izmailov, W Maddox, P Kirichenko, AG Wilson
Workshop on Invertible Neural Nets and Normalizing Flows, International …, 2019
122019
Task-agnostic continual learning with hybrid probabilistic models
P Kirichenko, M Farajtabar, D Rao, B Lakshminarayanan, N Levine, A Li, ...
Workshop on Invertible Neural Nets and Normalizing Flows, International …, 2021
82021
On Feature Learning in the Presence of Spurious Correlations
P Izmailov, P Kirichenko, N Gruver, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2022
22022
Effective Surrogate Models for Protein Design with Bayesian Optimization
N Gruver, S Stanton, P Kirichenko, M Finzi, P Maffettone, V Myers, ...
2021 ICML Workshop on Computational Biology, 2021
22021
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers
W Yang, P Kirichenko, M Goldblum, AG Wilson
arXiv preprint arXiv:2211.15231, 2022
2022
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Articles 1–11