
@inproceedings{adam_dual_2021,
	title = {Dual {Parameterization} of {Sparse} {Variational} {Gaussian} {Processes}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Adam, Vincent and Chang, Paul E. and Khan, Mohammad Emtiyaz and Solin, Arno},
	year = {2021}
}

@article{deisenroth_robust_2012,
	title = {Robust {Filtering} and {Smoothing} with {Gaussian} {Processes}},
	volume = {57},
	number = {7},
	journal = {IEEE Transactions on Automatic Control},
	author = {Deisenroth, Marc Peter and Turner, Ryan D. and Huber, Marco F. and Hanebeck, Uwe D. and Rasmussen, Carl Edward},
	year = {2012},
	pages = {1865--1871}
}

@article{longi_traversing_2021,
	title = {Traversing {Time} with {Multi}-{Resolution} {Gaussian} {Process} {State}-{Space} {Models}},
	journal = {arXiv preprint arXiv:2112.03230},
	author = {Longi, Krista and Lindinger, Jakob and Duennbier, Olaf and Kandemir, Melih and Klami, Arto and Rakitsch, Barbara},
	year = {2021}
}

@inproceedings{rossi_sparse_2021,
	title = {Sparse {Gaussian} {Processes} {Revisited}: {Bayesian} {Approaches} to {Inducing}-{Variable} {Approximations}},
	booktitle = {International {Conference} on {Artificial} {Intelligence} and {Statistics}},
	author = {Rossi, Simone and Heinonen, Markus and Bonilla, Edwin V. and Shen, Zheyang and Filippone, Maurizio},
	year = {2021}
}

@book{fletcher_practical_1987,
	title = {Practical {Methods} of {Optimization}},
	publisher = {Wiley},
	author = {Fletcher, R.},
	year = {1987}
}

@inproceedings{salimbeni_natural_2018,
	title = {Natural {Gradients} in {Practice}: {Non}-{Conjugate} {Variational} {Inference} in {Gaussian} {Process} {Models}},
	booktitle = {International {Conference} on {Artificial} {Intelligence} and {Statistics}},
	author = {Salimbeni, Hugh and Eleftheriadis, Stefanos and Hensman, James},
	year = {2018}
}

@inproceedings{kingma_adam:_2015,
	title = {Adam: {A} {Method} for {Stochastic} {Optimization}},
	booktitle = {International {Conference} on {Learning} {Representations}},
	author = {Kingma, Diederik P. and Ba, Jimmy},
	year = {2015}
}

@article{kalman_new_1960,
	title = {A {New} {Approach} to {Linear} {Filtering} and {Prediction} {Problems}},
	volume = {82},
	journal = {Transactions of the ASME–Journal of Basic Engineering},
	author = {Kalman, Rudolph Emil},
	year = {1960},
	pages = {35--45}
}

@inproceedings{yildiz_ode2vae:_2019,
	title = {{ODE}2VAE: {Deep} {Generative} {Second} {Order} {ODEs} with {Bayesian} {Neural} {Networks}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Yildiz, Cagatay and Heinonen, Markus and Lahdesmäki, Harri},
	year = {2019}
}

@inproceedings{lorraine_optimizing_2020,
	title = {Optimizing {Millions} of {Hyperparameters} by {Implicit} {Differentiation}},
	booktitle = {International {Conference} on {Artificial} {Intelligence} and {Statistics}},
	author = {Lorraine, Jonathan and Vicol, Paul and Duvenaud, David},
	year = {2020},
	file = {lorraine20a.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\FTEJIKR9\\lorraine20a.pdf:application/pdf;lorraine20a-supp.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\9XFJIHKS\\lorraine20a-supp.pdf:application/pdf}
}

@inproceedings{levine_continuous_2012,
	title = {Continuous {Inverse} {Optimal} {Control} with {Locally} {Optimal} {Examples}},
	booktitle = {International {Conference} on {Machine} {Learning}},
	author = {Levine, Sergey and Koltun, Vladlen},
	year = {2012},
	file = {cioc.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\5KDUMXJF\\cioc.pdf:application/pdf}
}

@article{kristensen_tmb_2016,
	title = {{TMB} : {Automatic} {Differentiation} and {Laplace} {Approximation}},
	volume = {70},
	number = {5},
	journal = {Journal of Statistical Software},
	author = {Kristensen, Kasper and Nielsen, Anders and Berg, Casper W. and Skaug, Hans and Bell, Bradley M.},
	year = {2016},
	pages = {1--21},
	file = {v70i05.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\5CSDF3VG\\v70i05.pdf:application/pdf}
}

@article{aicher_stochastic_2019,
	title = {Stochastic {Gradient} {MCMC} for {State} {Space} {Models}},
	volume = {1},
	number = {3},
	journal = {SIAM Journal on Mathematics of Data Science},
	author = {Aicher, Christopher and Ma, Yi-An and Foti, Nicholas J. and Fox, Emily B.},
	year = {2019},
	pages = {555--587},
	file = {18m1214780.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\76WVB4T5\\18m1214780.pdf:application/pdf}
}

@book{billings_nonlinear_2013,
	address = {Chichester, West Sussex, United Kingdom},
	title = {Nonlinear system identification: {NARMAX} methods in the time, frequency, and spatio-temporal domains},
	isbn = {978-1-118-53553-0 978-1-118-53554-7 978-1-118-53555-4},
	shorttitle = {Nonlinear system identification},
	publisher = {John Wiley \& Sons, Inc},
	author = {Billings, S. A.},
	year = {2013},
	keywords = {Mathematical models, Nonlinear systems, Nonlinear theories, Systems engineering},
	file = {ialongo19a.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\4X9B6GAK\\ialongo19a.pdf:application/pdf}
}

@inproceedings{ialongo_overcoming_2019,
	title = {Overcoming {Mean}-{Field} {Approximations} in {Recurrent} {Gaussian} {Process} {Models}},
	booktitle = {International {Conference} on {Machine} {Learning}},
	author = {Ialongo, Alessandro Davide and van der Wilk, Mark and Hensman, James and Rasmussen, Carl Edward},
	year = {2019},
	file = {ialongo19a.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\Z6HRG9QE\\ialongo19a.pdf:application/pdf}
}

@inproceedings{margossian_hamiltonian_2020,
	title = {Hamiltonian {Monte} {Carlo} using an adjoint-differentiated {Laplace} approximation: {Bayesian} inference for latent {Gaussian} models and beyond},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Margossian, Charles and Vehtari, Aki and Simpson, Daniel and Agrawal, Raj},
	year = {2020},
	file = {NeurIPS-2020-hamiltonian-monte-carlo-using-an-adjoint-differentiated-laplace-approximation-bayesian-inference-for-latent-gaussian-models-and-beyond-Paper.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\ST8GN8JG\\NeurIPS-2020-hamiltonian-monte-carlo-using-an-adjoint-differentiated-laplace-approximation-bayesian-inference-for-latent-gauss.pdf:application/pdf}
}

@inproceedings{doerr_probabilistic_2018,
	title = {Probabilistic {Recurrent} {State}-{Space} {Models}},
	booktitle = {International {Conference} on {Machine} {Learning}},
	author = {Doerr, Andreas and Daniel, Christian and Schiegg, Martin and Nguyen-Tuong, Duy and Schaal, Stefan and Toussaint, Marc and Sebastian, Trimpe},
	year = {2018},
	file = {doerr18a.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\QD8CJXCI\\doerr18a.pdf:application/pdf;doerr18a-supp.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\8W4A72AU\\doerr18a-supp.pdf:application/pdf}
}

@article{van_der_wilk_framework_2020,
	title = {A {Framework} for {Interdomain} and {Multioutput} {Gaussian} {Processes}},
	journal = {arXiv preprint arXiv:2003.01115},
	author = {van der Wilk, Mark and Dutordoir, Vincent and John, ST and Artemev, Artem and Adam, Vincent and Hensman, James},
	year = {2020}
}

@article{matthews_gpflow:_2017,
	title = {{GPflow}: {A} {Gaussian} process library using {TensorFlow}},
	volume = {18},
	number = {40},
	journal = {Journal of Machine Learning Research},
	author = {Matthews, Alexander G. de G. and van der Wilk, Mark and Nickson, Tom and Fujii, Keisuke. and Boukouvalas, Alexis and León-Villagrá, Pablo and Ghahramani, Zoubin and Hensman, James},
	year = {2017},
	pages = {1--6}
}

@inproceedings{abadi_tensorflow:_2016,
	title = {Tensorflow: a system for large-scale machine learning.},
	booktitle = {{USENIX} {Symposium} on {Operating} {Systems} {Design} and {Implementation}},
	author = {Abadi, Martín and Barham, Paul and Chen, Jianmin and Chen, Zhifeng and Davis, Andy and Dean, Jeffrey and Devin, Matthieu and Ghemawat, Sanjay and Irving, Geoffrey and Isard, Michael and {others}},
	year = {2016}
}

@book{sarkka_bayesian_2013,
	title = {Bayesian   {Filtering}   and   {Smoothing}},
	publisher = {Cambridge University Press},
	author = {Särkkä, Simo},
	year = {2013},
	file = {cup_book_online_20131111.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\DHRUCFE7\\cup_book_online_20131111.pdf:application/pdf}
}

@book{mackay_information_2003,
	title = {Information theory, inference and learning algorithms},
	publisher = {Cambridge University Press},
	author = {MacKay, David},
	year = {2003},
	file = {McKay - Information Theory, Inference, Learning Algorithms.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\IB2QAE5W\\McKay - Information Theory, Inference, Learning Algorithms.pdf:application/pdf}
}

@article{skaug_automatic_2006,
	title = {Automatic approximation of the marginal likelihood in non-{Gaussian} hierarchical models},
	volume = {51},
	number = {2},
	journal = {Computational Statistics \& Data Analysis},
	author = {Skaug, Hans J. and Fournier, David A.},
	year = {2006},
	pages = {699--709},
	file = {1-s2.0-S0167947306000764-main.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\BTNPAMPT\\1-s2.0-S0167947306000764-main.pdf:application/pdf}
}

@article{rue_approximate_2009,
	title = {Approximate {Bayesian} inference for latent {Gaussian} models by using integrated nested {Laplace} approximations},
	volume = {71},
	number = {2},
	journal = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
	author = {Rue, Håvard and Martino, Sara and Chopin, Nicolas},
	year = {2009},
	keywords = {Approximate Bayesian inference, Gaussian Markov random fields, Generalized additive mixed models, Laplace approximation, Parallel computing, Sparse matrices, Structured additive regression models},
	pages = {319--392},
	file = {j.1467-9868.2008.00700.x.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\3JA7JWX9\\j.1467-9868.2008.00700.x.pdf:application/pdf}
}

@inproceedings{frigola_bayesian_2013,
	title = {Bayesian {Inference} and {Learning} in {Gaussian} {Process} {State}-{Space} {Models} with {Particle} {MCMC}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Frigola, Roger and Lindsten, Fredrik and Schön, Thomas B and Rasmussen, Carl Edward},
	year = {2013},
	file = {NIPS-2013-bayesian-inference-and-learning-in-gaussian-process-state-space-models-with-particle-mcmc-Paper.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\3BGWNX9F\\NIPS-2013-bayesian-inference-and-learning-in-gaussian-process-state-space-models-with-particle-mcmc-Paper.pdf:application/pdf}
}

@book{rasmussen_gaussian_2006,
	series = {Adaptive computation and machine learning},
	title = {Gaussian {Processes} for {Machine} {Learning}},
	publisher = {MIT Press},
	author = {Rasmussen, C. E. and Williams, C. K. I.},
	year = {2006}
}

@inproceedings{eleftheriadis_identification_2017,
	title = {Identification of {Gaussian} {Process} {State} {Space} {Models}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Eleftheriadis, Stefanos and Nicholson, Tom and Deisenroth, Marc and Hensman, James},
	year = {2017},
	file = {NIPS-2017-identification-of-gaussian-process-state-space-models-Paper.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\AHVPH3UG\\NIPS-2017-identification-of-gaussian-process-state-space-models-Paper.pdf:application/pdf;supp_mat.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\DWFQQMHE\\supp_mat.pdf:application/pdf}
}

@inproceedings{frigola_variational_2014,
	title = {Variational {Gaussian} {Process} {State}-{Space} {Models}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Frigola, Roger and Chen, Yutian and Rasmussen, Carl E.},
	year = {2014},
	file = {NIPS-2014-variational-gaussian-process-state-space-models-Paper.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\SSI878FV\\NIPS-2014-variational-gaussian-process-state-space-models-Paper.pdf:application/pdf;vgpssm_supplementary_final.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\KNN2GR94\\vgpssm_supplementary_final.pdf:application/pdf}
}

@article{blei_variational_2016,
	title = {Variational {Inference}: {A} {Review} for {Statisticians}},
	volume = {112},
	number = {518},
	journal = {Journal of the American Statistical Association},
	author = {Blei, David and Kucukelbir, Alp and McAuliffe, Jon},
	year = {2016},
	pages = {859--877}
}

@inproceedings{snelson_sparse_2005,
	title = {Sparse {Gaussian} {Processes} using {Pseudo}-inputs},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Snelson, Edward and Ghahramani, Zoubin},
	year = {2005}
}

@inproceedings{titsias_variational_2009,
	title = {Variational {Learning} of {Inducing} {Variables} in {Sparse} {Gaussian} {Processes}},
	booktitle = {International {Conference} on {Artificial} {Intelligence} and {Statistics}},
	author = {Titsias, Michalis},
	year = {2009}
}

@inproceedings{hensman_gaussian_2013,
	title = {Gaussian {Processes} for {Big} {Data}},
	booktitle = {Conference on {Uncertainty} in {Artificial} {Intelligence}},
	author = {Hensman, James and Fusi, Nicolò and Lawrence, Neil D.},
	year = {2013}
}

@incollection{turner_two_2011,
	title = {Two problems with variational expectation maximisation for time-series models},
	booktitle = {Bayesian {Time} series models},
	publisher = {Cambridge University Press},
	author = {Turner, R. E. and Sahani, M.},
	year = {2011},
	pages = {109--130}
}

@phdthesis{frigola_bayesian_2015,
	title = {Bayesian time series learning with {Gaussian} processes},
	school = {University of Cambridge},
	author = {Frigola, Roger},
	year = {2015}
}

@article{molinari_determinants_2008,
	title = {Determinants of block tridiagonal matrices},
	volume = {429},
	number = {8},
	journal = {Linear Algebra and its Applications},
	author = {Molinari, Luca Guido},
	year = {2008},
	keywords = {Block tridiagonal matrix, Determinant, Transfer matrix},
	pages = {2221--2226},
	file = {1-s2.0-S0024379508003200-main.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\AUTQSN7J\\1-s2.0-S0024379508003200-main.pdf:application/pdf}
}

@article{salkuyeh_comments_2006,
	title = {Comments on “{A} note on a three-term recurrence for a tridiagonal matrix”},
	volume = {176},
	number = {2},
	journal = {Applied Mathematics and Computation},
	author = {Salkuyeh, Davod Khojasteh},
	year = {2006},
	keywords = {Block-tridiagonal, Determinant, Recurrence, Schur complement, Tridiagonal},
	pages = {442--444}
}

@article{koulaei_computing_2007,
	title = {On computing of block {ILU} preconditioner for block tridiagonal systems},
	volume = {202},
	number = {2},
	journal = {Journal of Computational and Applied Mathematics},
	author = {Koulaei, M. H. and Toutounian, F.},
	year = {2007},
	keywords = {Block ILU, Block tridiagonal matrices, Factored approximate inverses, Krylov subspace methods},
	pages = {248--257},
	file = {1-s2.0-S0377042706001269-main.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\NBU4B6FD\\1-s2.0-S0377042706001269-main.pdf:application/pdf}
}

@inproceedings{durrande_banded_2019,
	title = {Banded {Matrix} {Operators} for {Gaussian} {Markov} {Models} in the {Automatic} {Differentiation} {Era}},
	booktitle = {International {Conference} on {Artificial} {Intelligence} and {Statistics}},
	author = {Durrande, Nicolas and Adam, Vincent and Bordeaux, Lucas and Eleftheriadis, Stefanos and Hensman, James},
	year = {2019},
	file = {durrande19a.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\CXIP9I76\\durrande19a.pdf:application/pdf;durrande19a-supp.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\9IHE9QHH\\durrande19a-supp.pdf:application/pdf}
}

@article{bell_marginal_2000,
	title = {The marginal likelihood for parameters in a discrete {Gauss}-{Markov} process},
	volume = {48},
	number = {3},
	journal = {IEEE Transactions on Signal Processing},
	author = {Bell, Bradley M},
	year = {2000},
	pages = {870--873},
	file = {The_marginal_likelihood_for_parameters_in_a_discrete_Gauss-Markov_process.pdf:C\:\\Users\\LJA2RNG\\AppData\\Roaming\\CR Culture Impulses\\Zotero for Bosch\\Profiles\\eznmwzzd.default\\zotero\\storage\\BSK9ZRN5\\The_marginal_likelihood_for_parameters_in_a_discrete_Gauss-Markov_process.pdf:application/pdf}
}

@book{krantz_implicit_2002,
	title = {The implicit function theorem: history, theory, and applications},
	publisher = {Springer Science \& Business Media},
	author = {Krantz, Steven George and Parks, Harold R},
	year = {2002}
}

@inproceedings{kingma_auto-encoding_2014,
	title = {Auto-{Encoding} {Variational} {Bayes}},
	booktitle = {International {Conference} on {Learning} {Representations}},
	author = {Kingma, Diederik and Welling, Max},
	year = {2014}
}

@inproceedings{cremer_inference_2018,
	title = {Inference suboptimality in variational autoencoders},
	booktitle = {International {Conference} on {Machine} {Learning}},
	author = {Cremer, Chris and Li, Xuechen and Duvenaud, David},
	year = {2018}
}

@article{wang_gaussian_2007,
	title = {Gaussian process dynamical models for human motion},
	volume = {30},
	number = {2},
	journal = {IEEE transactions on pattern analysis and machine intelligence},
	author = {Wang, Jack M and Fleet, David J and Hertzmann, Aaron},
	year = {2007},
	pages = {283--298}
}

@article{hoffman_stochastic_2013,
	title = {Stochastic variational inference.},
	volume = {14},
	number = {5},
	journal = {Journal of Machine Learning Research},
	author = {Hoffman, Matthew D and Blei, David M and Wang, Chong and Paisley, John},
	year = {2013}
}

@inproceedings{bayer_mind_2021,
	title = {Mind the {Gap} when {Conditioning} {Amortised} {Inference} in {Sequential} {Latent}-{Variable} {Models}},
	booktitle = {International {Conference} on {Learning} {Representations}},
	author = {Bayer, Justin and Soelch, Maximilian and Mirchev, Atanas and Kayalibay, Baris and van der Smagt, Patrick},
	year = {2021}
}

@inproceedings{ko_gp-ukf:_2007,
	title = {{GP}-{UKF}: {Unscented} {Kalman} filters with {Gaussian} process prediction and observation models},
	booktitle = {{IEEE}/{RSJ} {International} {Conference} on {Intelligent} {Robots} and {Systems}},
	author = {Ko, Jonathan and Klein, Daniel J and Fox, Dieter and Haehnel, Dirk},
	year = {2007}
}

@inproceedings{wang_gaussian_2005,
	title = {Gaussian {Process} {Dynamical} {Models}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Wang, Jack and Hertzmann, Aaron and Fleet, David J},
	year = {2005}
}

@inproceedings{ritter_scalable_2018,
	title = {A {Scalable} {Laplace} {Approximation} for {Neural} {Networks}},
	booktitle = {International {Conference} on {Learning} {Representations}},
	author = {Ritter, Hippolyt and Botev, Aleksandar and Barber, David},
	year = {2018}
}

@article{unlu_gradient_2021,
	title = {Gradient {Regularization} as {Approximate} {Variational} {Inference}},
	volume = {23},
	number = {12},
	journal = {Entropy},
	author = {Unlu, Ali and Aitchison, Laurence},
	year = {2021},
	pages = {1629}
}

@article{gould_deep_2019,
	title = {Deep {Declarative} {Networks}: {A} {New} {Hope}},
	journal = {arXiv preprint arXiv:1909.04866},
	author = {Gould, Stephen and Hartley, Richard and Campbell, Dylan},
	year = {2019},
	note = {arXiv: 1909.04866}
}

@inproceedings{tomczak_collapsed_2021,
	title = {Collapsed {Variational} {Bounds} for {Bayesian} {Neural} {Networks}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Tomczak, Marcin B and Swaroop, Siddharth and Foong, Andrew Y K and Turner, Richard E},
	year = {2021}
}

@article{quinonero-candela_unifying_2005,
	title = {A unifying view of sparse approximate {Gaussian} process regression},
	volume = {6},
	number = {65},
	journal = {The Journal of Machine Learning Research},
	author = {Quinonero-Candela, Joaquin and Rasmussen, Carl Edward},
	year = {2005},
	pages = {1939--1959}
}

@inproceedings{lindinger_beyond_2020,
	title = {Beyond the {Mean}-{Field}: {Structured} {Deep} {Gaussian} {Processes} {Improve} the {Predictive} {Uncertainties}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Lindinger, Jakob and Reeb, David and Lippert, Christoph and Rakitsch, Barbara},
	year = {2020}
}

@inproceedings{deisenroth_pilco:_2011,
	title = {{PILCO}: {A} {Model}-{Based} and {Data}-{Efficient} {Approach} to {Policy} {Search}},
	booktitle = {International {Conference} on {Machine} {Learning}},
	author = {Deisenroth, Marc Peter and Rasmussen, Carl Edward},
	year = {2011}
}