@inproceedings{vanderouderaa2023learning,
  title = "Learning Layer-wise Equivariances Automatically using Gradients",
  author = "Tycho F. A. van der Ouderaa and Alexander Immer and Mark van der Wilk",
  year = "2023",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  month = "Dec",
  volume = "36",
}
@misc{green2023current,
  title = "Current Methods for Drug Property Prediction in the Real World",
  author = "Jacob Green and Cecilia Cabrera Diaz and Maximilian A. H. Jakobs and Andrea Dimitracopoulos and Mark van der Wilk and Ryan D. Greenhalgh",
  year = "2023",
}
@inproceedings{immer2023stochmarglik,
  title = "Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels",
  author = "Immer, Alexander and Van Der Ouderaa, Tycho F. A. and Van Der Wilk, Mark and Ratsch, Gunnar and Sch\"{o}lkopf, Bernhard",
  year = "2023",
  booktitle = "Proceedings of the 40th International Conference on Machine Learning",
  url = "https://proceedings.mlr.press/v202/immer23b.html",
}
@misc{dhir2023causal,
  title = "Causal Discovery using Bayesian Model Selection",
  author = "Anish Dhir and Mark van der Wilk",
  year = "2023",
}
@inproceedings{cunningham2023actuallysparse,
  title = "Actually Sparse Variational Gaussian Processes",
  author = "Cunningham, Harry Jake and de Souza, Daniel Augusto and Takao, So and van der Wilk, Mark and Deisenroth, Marc Peter",
  year = "2023",
  booktitle = "Proceedings of The 26th International Conference on Artificial Intelligence and Statistics",
  url = "https://proceedings.mlr.press/v206/cunningham23a.html",
}
@article{goertz2023can,
  title = "Competitive Amplification Networks enable molecular pattern recognition with PCR",
  author = "John P Goertz and Ruby Sedgwick and Francesca Smith and Myrsini Kaforou and Victoria J Wright and Jethro A. Herberg and Zsofia Kote-Jarai and Ros Eeles and Mike Levin and Ruth Misener and Mark van der Wilk and Molly M Stevens",
  year = "2023",
  journal = "bioRxiv",
  publisher = "Cold Spring Harbor Laboratory",
  url = "https://www.biorxiv.org/content/early/2023/07/01/2023.06.29.546934",
  doi = "10.1101/2023.06.29.546934",
}
@article{folch2023combining,
  title = "Combining multi-fidelity modelling and asynchronous batch Bayesian Optimization",
  author = "Jose Pablo Folch and Robert M. Lee and Behrang Shafei and David Walz and Calvin Tsay and Mark {van der Wilk} and Ruth Misener",
  year = "2023",
  journal = "Computers & Chemical Engineering",
  url = "https://www.sciencedirect.com/science/article/pii/S0098135423000637",
  volume = "172",
  doi = "https://doi.org/10.1016/j.compchemeng.2023.108194",
}
@incollection{dhir2022causal,
  title = "Causal Discovery using Marginal Likelihood",
  author = "Anish Dhir and Mark van der Wilk",
  year = "2022",
  booktitle = "NeurIPS Workshop on Causality for Real-world Impact",
  url = "https://openreview.net/forum?id=k0DJZXMSgH4",
}
@incollection{ouderaa2022sparse,
  title = "Sparse Convolutions on Lie Groups",
  author = "van der Ouderaa, Tycho FA and van der Wilk, Mark",
  year = "2022",
  booktitle = "NeurIPS Workshop on Symmetry and Geometry in Neural Representations",
  month = "Dec",
  url = "https://openreview.net/pdf?id=aCYzMmNK6tK",
}
@misc{terenin2022numerically,
  title = "Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees",
  author = "Terenin, Alexander and Burt, David R. and Artemev, Artem and Flaxman, Seth and van der Wilk, Mark and Rasmussen, Carl Edward and Ge, Hong",
  year = "2022",
  keywords = "Machine Learning (stat.ML), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences",
  publisher = "arXiv",
  url = "https://arxiv.org/abs/2210.07893",
  doi = "10.48550/ARXIV.2210.07893",
}
@incollection{ober2022recommendations,
  title = "Recommendations for Baselines and Benchmarking Approximate Gaussian Processes",
  author = "Ober, Sebastian W and Burt, David R and Artemev, Artem and van der Wilk, Mark",
  year = "2022",
  booktitle = "NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems",
  month = "dec",
  url = "https://gp-seminar-series.github.io/assets/camera_ready/62.pdf",
}
@inproceedings{ouderaa2022relaxing,
  title = "Relaxing Equivariance Constraints with Non-stationary Continuous Filters",
  author = "van der Ouderaa, Tycho F. A. and Romero, David W. and van der Wilk, Mark",
  year = "2022",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  month = "Dec",
  url = "https://arxiv.org/abs/2204.07178",
  volume = "35",
  doi = "10.48550/ARXIV.2204.07178",
}
@inproceedings{folch2022snake,
  title = "SnAKe: Bayesian Optimization with Pathwise Exploration",
  author = "Folch, Jose Pablo and Zhang, Shiqiang and Lee, Robert M and Shafei, Behrang and Walz, David and Tsay, Calvin and van der Wilk, Mark and Misener, Ruth",
  year = "2022",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  month = "Dec",
  url = "https://arxiv.org/abs/2202.00060",
  volume = "35",
  doi = "10.48550/ARXIV.2202.00060",
}
@inproceedings{immerouderaa2022deepinv,
  title = "Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations",
  author = "Immer, Alexander and van der Ouderaa, Tycho F. A. and Rätsch, Gunnar and Fortuin, Vincent and van der Wilk, Mark",
  year = "2022",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  month = "Dec",
  url = "https://arxiv.org/abs/2202.10638",
  volume = "35",
  doi = "10.48550/ARXIV.2202.10638",
}
@inproceedings{artemev2022xla,
  title = "Memory Safe Computations with XLA Compiler",
  author = "Artemev, Artem and Roeder, Tilman and van der Wilk, Mark",
  year = "2022",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  month = "Dec",
  url = "https://arxiv.org/abs/2206.14148",
  volume = "35",
  doi = "10.48550/ARXIV.2206.14148",
}
@incollection{popescu2022tproc,
  title = "Matrix Inversion free variational inference in Conditional Student's T Processes",
  author = "Sebastian Popescu and Ben Glocker and Mark van der Wilk",
  year = "2022",
  booktitle = "Fourth Symposium on Advances in Approximate Bayesian Inference",
  month = "feb",
  url = "https://openreview.net/forum?id=jLLR71k9Hsi",
}
@incollection{vdw2022inv,
  title = "Improved Inverse-Free Variational Bounds for Sparse Gaussian Processes",
  author = "Mark van der Wilk and Artem Artemev and James Hensman",
  year = "2022",
  booktitle = "Fourth Symposium on Advances in Approximate Bayesian Inference",
  month = "feb",
  url = "https://openreview.net/forum?id=t2vxi9fNhKu",
}
@inproceedings{ouderaa2022learning,
  title = "Learning invariant weights in neural networks",
  author = "van der Ouderaa, Tycho F.A. and van der Wilk, Mark",
  year = "2022",
  booktitle = "Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI)",
  editor = "Cussens, James and Zhang, Kun",
  month = "Aug",
  pages = "1992--2001",
  publisher = "PMLR",
  series = "Proceedings of Machine Learning Research",
  url = "https://proceedings.mlr.press/v180/ouderaa22a.html",
  volume = "180",
}
@inproceedings{nabarro2022data,
  title = "Data augmentation in Bayesian neural networks and the cold posterior effect",
  author = "Seth Nabarro and Stoil Ganev and Adrià Garriga-Alonso and Vincent Fortuin and Mark van der Wilk and Laurence Aitchison",
  year = "2022",
  booktitle = "Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI)",
  month = "Aug",
  url = "https://arxiv.org/abs/2106.05586",
}
@inproceedings{schwoebel2022layer,
  title = "Last Layer Marginal Likelihood for Invariance Learning",
  author = "Pola Schwöbel and Martin Jørgensen and Sebastian W. Ober and Mark van der Wilk",
  year = "2022",
  booktitle = "Proceedings of the Twenty Fifth International Conference on Artificial Intelligence and Statistics (AISTATS)",
  url = "https://arxiv.org/abs/2106.07512",
}
@inproceedings{fortuin2022bayesian,
  title = "Bayesian Neural Network Priors Revisited",
  author = "Vincent Fortuin and Adri{\`a} Garriga-Alonso and Sebastian W. Ober and Florian Wenzel and Gunnar Ratsch and Richard E Turner and Mark van der Wilk and Laurence Aitchison",
  year = "2022",
  booktitle = "International Conference on Learning Representations (ICLR)",
  url = "https://openreview.net/forum?id=xkjqJYqRJy",
}
@inproceedings{ru2021speed,
  title = "Speedy Performance Estimation for Neural Architecture Search",
  author = "Binxin Ru and Clare Lyle and Lisa Schut and Miroslav Fil and Mark van der Wilk and Yarin Gal",
  year = "2021",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  url = "https://arxiv.org/abs/2006.04492",
  volume = "34",
}
@inproceedings{dutordoir2021relu,
  title = "Deep Neural Networks as Point Estimates for Deep Gaussian Processes",
  author = "Vincent Dutordoir and James Hensman and Mark van der Wilk and Carl Henrik Ek and Zoubin Ghahramani and Nicolas Durrande",
  year = "2021",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  url = "https://arxiv.org/abs/2105.04504",
  volume = "34",
}
@misc{burt2021barely,
  title = "Barely Biased Learning for Gaussian Process Regression",
  author = "David R. Burt and Artem Artemev and Mark van der Wilk",
  year = "2021",
  url = "https://arxiv.org/abs/2109.09417",
}
@inproceedings{artemevburt2021cglb,
  title = "Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients",
  author = "Artemev, Artem and Burt, David R. and van der Wilk, Mark",
  year = "2021",
  booktitle = "Proceedings of the 38th International Conference on Machine Learning (ICML)",
  editor = "Meila, Marina and Zhang, Tong",
  month = "Jul",
  pages = "362--372",
  publisher = "PMLR",
  series = "Proceedings of Machine Learning Research",
  url = "https://proceedings.mlr.press/v139/artemev21a.html",
  volume = "139",
}
@inproceedings{garriga-alonso2021correlated,
  title = "Correlated weights in infinite limits of deep convolutional neural networks",
  author = "Garriga-Alonso, Adri\`a and van der Wilk, Mark",
  year = "2021",
  booktitle = "Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence",
  editor = "de Campos, Cassio and Maathuis, Marloes H.",
  month = "Jul",
  pages = "1998--2007",
  publisher = "PMLR",
  series = "Proceedings of Machine Learning Research",
  url = "https://proceedings.mlr.press/v161/garriga-alonso21a.html",
  volume = "161",
}
@inproceedings{ober2021promises,
  title = "The promises and pitfalls of deep kernel learning",
  author = "Ober, Sebastian W. and Rasmussen, Carl E. and van der Wilk, Mark",
  year = "2021",
  booktitle = "Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence (UAI)",
  editor = "de Campos, Cassio and Maathuis, Marloes H.",
  month = "Jul",
  pages = "1206--1216",
  publisher = "PMLR",
  series = "Proceedings of Machine Learning Research",
  url = "https://proceedings.mlr.press/v161/ober21a.html",
  volume = "161",
}
@misc{dutordoir2021gpflux,
  title = "GPflux: A Library for Deep Gaussian Processes",
  author = "Vincent Dutordoir and Hugh Salimbeni and Eric Hambro and John McLeod and Felix Leibfried and Artem Artemev and Mark van der Wilk and James Hensman and Marc P. Deisenroth and ST John",
  year = "2021",
  url = "https://arxiv.org/abs/2104.05674",
}
@incollection{burt2020understanding,
  title = "Understanding Variational Inference in Function-Space",
  author = "David R. Burt and Sebastian W. Ober and Adri{\`a} Garriga-Alonso and Mark van der Wilk",
  year = "2021",
  booktitle = "Third Symposium on Advances in Approximate Bayesian Inference",
  month = "jan",
  url = "https://arxiv.org/abs/2011.09421",
}
@inproceedings{lyle2020trainingspeed,
  title = "A Bayesian Perspective on Training Speed and Model Selection",
  author = "Lyle, Clare and Schut, Lisa and Ru, Robin and Gal, Yarin and van der Wilk, Mark",
  year = "2020",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  editor = "H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin",
  pages = "10396--10408",
  publisher = "Curran Associates, Inc.",
  url = "https://proceedings.neurips.cc/paper/2020/file/75a7c30fc0063c4952d7eb044a3c0897-Paper.pdf",
  volume = "33",
}
@misc{smith2020capsules,
  title = "Capsule Networks -- A Probabilistic Perspective",
  author = "Lewis Smith and Lisa Schut and Yarin Gal and Mark van der Wilk",
  year = "2020",
  url = "https://arxiv.org/abs/2004.03553",
}
@misc{burt2020vof,
  title = "Variational Orthogonal Features",
  author = "David R. Burt and Carl Edward Rasmussen and Mark van der Wilk",
  year = "2020",
  url = "https://arxiv.org/abs/2006.13170",
}
@inproceedings{monteiro2020correlated,
  title = "Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty",
  author = "Monteiro, Miguel and Le Folgoc, Loic and Coelho de Castro, Daniel and Pawlowski, Nick and Marques, Bernardo and Kamnitsas, Konstantinos and van der Wilk, Mark and Glocker, Ben",
  year = "2020",
  booktitle = "Advances in Neural Information Processing Systems (NeurIPS)",
  editor = "H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin",
  pages = "12756--12767",
  publisher = "Curran Associates, Inc.",
  url = "https://proceedings.neurips.cc/paper/2020/file/95f8d9901ca8878e291552f001f67692-Paper.pdf",
  volume = "33",
}
@article{burt2020convergence,
  title = "Convergence of Sparse Variational Inference in Gaussian Processes Regression",
  author = "David R. Burt and Carl Edward Rasmussen and Mark van der Wilk",
  year = "2020",
  journal = "Journal of Machine Learning Research",
  number = "131",
  pages = "1-63",
  url = "http://jmlr.org/papers/v21/19-1015.html",
  volume = "21",
}
@misc{lyle2020benefits,
  title = "On the Benefits of Invariance in Neural Networks",
  author = "Clare Lyle and Mark van der Wilk and Marta Kwiatkowska and Yarin Gal and Benjamin Bloem-Reddy",
  year = "2020",
  url = "https://arxiv.org/abs/2005.00178",
}
@misc{vdw2020framework,
  title = "A Framework for Interdomain and Multioutput Gaussian Processes",
  author = "Mark van der Wilk and Vincent Dutordoir and ST John and Artem Artemev and Vincent Adam and James Hensman",
  year = "2020",
  url = "https://arxiv.org/abs/2003.01115",
}
@inproceedings{dutordoir2020dcgp,
  title = "Bayesian Image Classification with Deep Convolutional Gaussian Processes",
  author = "Dutordoir, Vincent and van der Wilk, Mark and Artemev, Artem and Hensman, James",
  year = "2020",
  booktitle = "Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS)",
  editor = "Chiappa, Silvia and Calandra, Roberto",
  month = "Aug",
  pages = "1529--1539",
  publisher = "PMLR",
  series = "Proceedings of Machine Learning Research",
  url = "http://proceedings.mlr.press/v108/dutordoir20a.html",
  volume = "108",
}
@misc{sedgwick2020design,
  title = "Design of Experiments for Verifying Biomolecular Networks",
  author = "Ruby Sedgwick and John Goertz and Molly Stevens and Ruth Misener and Mark van der Wilk",
  year = "2020",
  url = "https://arxiv.org/abs/2011.10575",
}
@inproceedings{vdw2020inv,
  title = "Variational Gaussian Process Models without Matrix Inverses",
  author = "van der Wilk, Mark and John, ST and Artemev, Artem and Hensman, James",
  year = "2020",
  booktitle = "Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference",
  editor = "Zhang, Cheng and Ruiz, Francisco and Bui, Thang and Dieng, Adji Bousso and Liang, Dawen",
  month = "Jan",
  pages = "1--9",
  publisher = "PMLR",
  series = "Proceedings of Machine Learning Research",
  url = "http://proceedings.mlr.press/v118/wilk20a.html",
  volume = "118",
}
@inproceedings{heaukulani2019wishart,
  title = "Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes",
  author = "Heaukulani, Creighton and van der Wilk, Mark",
  year = "2019",
  booktitle = "Advances in Neural Information Processing Systems 32 (NeurIPS)",
  editor = "H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett",
  publisher = "Curran Associates, Inc.",
  url = "https://proceedings.neurips.cc/paper/2019/file/5b168fdba5ee5ea262cc2d4c0b457697-Paper.pdf",
  volume = "32",
}
@phdthesis{vdw2019sparse,
  title = "Sparse Gaussian process approximations and applications",
  author = "Van der Wilk and Mark",
  year = "2019",
  school = "University of Cambridge",
  url = "https://www.repository.cam.ac.uk/handle/1810/288347",
}
@inproceedings{ialongo2019overcoming,
  title = "Overcoming Mean-Field Approximations in Recurrent {G}aussian Process Models",
  author = "Ialongo, Alessandro Davide and van der Wilk, Mark and Hensman, James and Rasmussen, Carl Edward",
  year = "2019",
  booktitle = "Proceedings of the 36th International Conference on Machine Learning (ICML)",
  editor = "Kamalika Chaudhuri and Ruslan Salakhutdinov",
  month = "Jun",
  pages = "2931--2940",
  publisher = "PMLR",
  series = "Proceedings of Machine Learning Research",
  url = "http://proceedings.mlr.press/v97/ialongo19a.html",
  volume = "97",
}
@inproceedings{burt2019rates,
  title = "Rates of Convergence for Sparse Variational {G}aussian Process Regression",
  author = "Burt, David and Rasmussen, Carl Edward and van der Wilk, Mark",
  year = "2019",
  booktitle = "Proceedings of the 36th International Conference on Machine Learning (ICML)",
  editor = "Kamalika Chaudhuri and Ruslan Salakhutdinov",
  month = "Jun",
  pages = "862--871",
  publisher = "PMLR",
  series = "Proceedings of Machine Learning Research",
  url = "http://proceedings.mlr.press/v97/burt19a.html",
  volume = "97",
}
@inproceedings{tran2019layers,
  title = "Bayesian Layers: A Module for Neural Network Uncertainty",
  author = "Tran, Dustin and Dusenberry, Mike and van der Wilk, Mark and Hafner, Danijar",
  year = "2019",
  booktitle = "Advances in Neural Information Processing Systems 32 (NeurIPS)",
  editor = "H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett",
  publisher = "Curran Associates, Inc.",
  url = "https://proceedings.neurips.cc/paper/2019/file/154ff8944e6eac05d0675c95b5b8889d-Paper.pdf",
  volume = "32",
}
@inproceedings{vdw2018invgp,
  title = "Learning Invariances using the Marginal Likelihood",
  author = "van der Wilk, Mark and Bauer, Matthias and John, ST and Hensman, James",
  year = "2018",
  booktitle = "Advances in Neural Information Processing Systems 31 (NeurIPS)",
  editor = "S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett",
  pages = "9960--9970",
  publisher = "Curran Associates, Inc.",
  url = "http://papers.nips.cc/paper/8199-learning-invariances-using-the-marginal-likelihood.pdf",
}
@incollection{ialongo2017closed,
  title = "Closed-form Inference and Prediction in {G}aussian Process State-Space Models",
  author = "Alessandro Davide Ialongo and Mark van der Wilk and Carl Edward Rasmussen",
  year = "2017",
  booktitle = "NIPS 2017 Workshop on Time Series",
  url = "https://arxiv.org/abs/1812.03580",
}
@inproceedings{mcallister2017concrete,
  title = "Concrete problems for autonomous vehicle safety: advantages of {B}ayesian deep learning",
  author = "McAllister, Rowan and Gal, Yarin and Kendall, Alex and van der Wilk, Mark and Shah, Amar and Cipolla, Roberto and Weller, Adrian Vivian",
  year = "2017",
  organization = "International Joint Conferences on Artificial Intelligence",
  url = "https://www.ijcai.org/Proceedings/2017/0661.pdf",
}
@inproceedings{vdw2017convgp,
  title = "Convolutional {G}aussian Processes",
  author = "van der Wilk, Mark and Rasmussen, Carl Edward and Hensman, James",
  year = "2017",
  booktitle = "Advances in Neural Information Processing Systems 30 (NIPS)",
  editor = "I. Guyon and U. V. Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett",
  pages = "2849--2858",
  publisher = "Curran Associates, Inc.",
  url = "http://papers.nips.cc/paper/6877-convolutional-gaussian-processes.pdf",
}
@article{gpflow,
  title = "{GPflow}: A {G}aussian Process Library using {T}ensor{F}low",
  author = "Alexander G. de G. Matthews and Mark van der Wilk and Tom Nickson and Keisuke Fujii and Alexis Boukouvalas and Pablo Le{{\'o}}n-Villagr{{\'a}} and Zoubin Ghahramani and James Hensman",
  year = "2017",
  journal = "Journal of Machine Learning Research",
  number = "40",
  pages = "1-6",
  url = "http://jmlr.org/papers/v18/16-537.html",
  volume = "18",
}
@incollection{mcallister2016exploration,
  title = "Data-Efficient Policy Search using {PILCO} and Directed-Exploration",
  author = "Rowan McAllister and Mark van der Wilk and Carl Edward Rasmussen",
  year = "2016",
  booktitle = "ICML 2016 Workshop on Data-Efficient Machine Learning",
  url = "https://drive.google.com/open?id=0B0VXvxUNyiVSQ01VUXIzdXQ4MW8",
}
@inproceedings{bauer2016understanding,
  title = "Understanding Probabilistic Sparse {G}aussian Process Approximations",
  author = "Bauer, Matthias and van der Wilk, Mark and Rasmussen, Carl Edward",
  year = "2016",
  booktitle = "Advances in Neural Information Processing Systems 29 (NIPS)",
  editor = "D. D. Lee and M. Sugiyama and U. V. Luxburg and I. Guyon and R. Garnett",
  pages = "1533--1541",
  publisher = "Curran Associates, Inc.",
  url = "http://papers.nips.cc/paper/6477-understanding-probabilistic-sparse-gaussian-process-approximations.pdf",
}
@incollection{vdw2014wplvm,
  title = "Variational Inference for Latent Variable Modelling of Correlation Structure",
  author = "Mark van der Wilk and Andrew Gordon Wilson and Carl Edward Rasmussen",
  year = "2014",
  booktitle = "NIPS 2014 Workshop of Advances in Variational Inference",
  url = "https://drive.google.com/file/d/0BwY-r_90KHY4Vmd4UzBhbEI0RWM/view?usp=sharing",
}
@misc{galvdw2014tutorial,
  title = "Variational Inference in Sparse {G}aussian Process Regression and Latent Variable Models - a Gentle Tutorial",
  author = "Yarin Gal and Mark van der Wilk",
  year = "2014",
  url = "https://arxiv.org/abs/1402.1412",
}
@inproceedings{gal2014parallel,
  title = "Distributed Variational Inference in Sparse {G}aussian Process Regression and Latent Variable Models",
  author = "Yarin Gal and Mark van der Wilk and Carl Edward Rasmussen",
  year = "2014",
  booktitle = "Advances in Neural Information Processing Systems 27 (NIPS)",
  editor = "Z. Ghahramani and M. Welling and C. Cortes and N. D. Lawrence and K. Q. Weinberger",
  pages = "3257--3265",
  publisher = "Curran Associates, Inc.",
  url = "http://papers.nips.cc/paper/5593-distributed-variational-inference-in-sparse-gaussian-process-regression-and-latent-variable-models.pdf",
}