commit bb9ebecedce12fe23a97324a09c0224fe92ebe21
parent ddd91b02d9d252ecf06a91dc5d44b3ae2f35b568
Author: Silas Brack <s174433@student.dtu.dk>
Date: Thu, 26 Jan 2023 15:35:13 +0100
Fixed bibliography.
Diffstat:
| M | main.bib | | | 66 | +++++++++++++++++++++++++++++++++--------------------------------- |
1 file changed, 33 insertions(+), 33 deletions(-)
diff --git a/main.bib b/main.bib
@@ -1,19 +1,19 @@
@inproceedings{bach2013sharp,
- title = {Sharp analysis of low-rank kernel matrix approximations},
+ title = {Sharp Analysis of Low-Rank Kernel Matrix Approximations},
author = {Bach, Francis},
booktitle = colt,
year = {2013}
}
@book{bishop1995neural,
- title = {Neural networks for pattern recognition},
+ title = {Neural Networks for Pattern Recognition},
author = {Bishop, Christopher},
year = {1995},
publisher = {Oxford University Press}
}
@inproceedings{botev2017practical,
- title = {Practical {G}auss-{N}ewton optimisation for deep learning},
+ title = {Practical {G}auss-{N}ewton Optimisation for Deep Learning},
author = {Botev, Aleksandar and Ritter, Hippolyt and Barber, David},
booktitle = icml,
year = {2017}
@@ -27,14 +27,14 @@
}
@article{denker1990transforming,
- title = {Transforming neural-net output levels to probability distributions},
+ title = {Transforming Neural-Net Output Levels to Probability Distributions},
author = {Denker, John and LeCun, Yann},
journal = nips,
year = {1990}
}
@article{fong2020marginal,
- title = {On the marginal likelihood and cross-validation},
+ title = {On the Marginal Likelihood and Cross-Validation},
author = {Fong, Edwin and Holmes, Chris C},
journal = {Biometrika},
volume = {107},
@@ -45,14 +45,14 @@
}
@inproceedings{gardner2018gpytorch,
- title = {{GP}yTorch: Blackbox Matrix-Matrix Gaussian Process Inference with {GPU} Acceleration},
+ title = {{GP}yTorch: Blackbox Matrix-Matrix Gaussian Process Inference With {GPU} Acceleration},
author = {Gardner, Jacob and Pleiss, Geoff and Weinberger, Kilian Q and Bindel, David and Wilson, Andrew G},
booktitle = nips,
year = {2018}
}
@article{giordano2018covariances,
- title = {Covariances, robustness and variational bayes},
+ title = {Covariances, Robustness and Variational Bayes},
author = {Giordano, Ryan and Broderick, Tamara and Jordan, Michael I},
journal = jmlr,
volume = {19},
@@ -61,7 +61,7 @@
}
@article{hale2008computing,
- title = {Computing $A^\alpha$, $\log(A)$, and related matrix functions by contour integrals},
+ title = {Computing $A^\alpha$, $\log(A)$, and Related Matrix Functions by Contour Integrals},
author = {Hale, Nicholas and Higham, Nicholas J and Trefethen, Lloyd N},
journal = {SIAM Journal on Numerical Analysis},
volume = {46},
@@ -72,7 +72,7 @@
}
@article{harbrecht2012low,
- title = {On the low-rank approximation by the pivoted {C}holesky decomposition},
+ title = {On the Low-Rank Approximation by the Pivoted {C}holesky Decomposition},
author = {Harbrecht, Helmut and Peters, Michael and Schneider, Reinhold},
journal = {Applied numerical mathematics},
volume = {62},
@@ -83,7 +83,7 @@
}
@article{heskes2000natural,
- title = {On ``natural'' learning and pruning in multilayered perceptrons},
+ title = {On ``Natural'' Learning and Pruning in Multilayered Perceptrons},
author = {Heskes, Tom},
journal = {Neural Computation},
volume = {12},
@@ -94,7 +94,7 @@
}
@article{hochreiter1997flat,
- title = {Flat minima},
+ title = {Flat Minima},
author = {Hochreiter, Sepp and Schmidhuber, J{\"u}rgen},
journal = {Neural computation},
volume = {9},
@@ -105,14 +105,14 @@
}
@inproceedings{immer2021scalable,
- title = {Scalable marginal likelihood estimation for model selection in deep learning},
+ title = {Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning},
author = {Immer, Alexander and Bauer, Matthias and Fortuin, Vincent and R{\"a}tsch, Gunnar and Emtiyaz, Khan Mohammad},
booktitle = icml,
year = {2021}
}
@article{izzatullah2022laplace,
- title = {Laplace {H}ypo{PINN}: physics-informed neural network for hypocenter localization and its predictive uncertainty},
+ title = {Laplace {H}ypo{PINN}: Physics-Informed Neural Network for Hypocenter Localization and Its Predictive Uncertainty},
author = {Izzatullah, Muhammad and Yildirim, Isa Eren and Waheed, Umair Bin and Alkhalifah, Tariq},
journal = {Machine Learning: Science and Technology},
volume = {3},
@@ -124,7 +124,7 @@
@software{jax2018github,
author = {James Bradbury and Roy Frostig and Peter Hawkins and Matthew James Johnson and Chris Leary and Dougal Maclaurin and George Necula and Adam Paszke and Jake Vander{P}las and Skye Wanderman-{M}ilne and Qiao Zhang},
- title = {{JAX}: composable transformations of {P}ython+{N}um{P}y programs},
+ title = {{JAX}: Composable Transformations of {P}ython+{N}um{P}y Programs},
url = {http://github.com/google/jax},
version = {0.3.13},
year = {2018}
@@ -138,28 +138,28 @@
}
@article{keskar2016large,
- title = {On large-batch training for deep learning: Generalization gap and sharp minima},
+ title = {On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima},
author = {Keskar, Nitish Shirish and Mudigere, Dheevatsa and Nocedal, Jorge and Smelyanskiy, Mikhail and Tang, Ping Tak Peter},
journal = {arXiv preprint arXiv:1609.04836},
year = {2016}
}
@inproceedings{kingma2014adam,
- title = {Adam: A method for stochastic optimization},
+ title = {Adam: A Method for Stochastic Optimization},
author = {Kingma, Diederik P and Ba, Jimmy},
booktitle = iclr,
year = {2015}
}
@inproceedings{kunstner2019limitations,
- title = {Limitations of the empirical {F}isher approximation for natural gradient descent},
+ title = {Limitations of the Empirical {F}isher Approximation for Natural Gradient Descent},
author = {Kunstner, Frederik and Hennig, Philipp and Balles, Lukas},
booktitle = nips,
year = {2019}
}
@article{laplace1774memoire,
- title = {M\'emoire sur la probabilit\'e des causes par les \'ev\'enements},
+ title = {M\'emoire Sur La Probabilit\'e Des Causes Par Les \'Ev\'enements},
author = {Laplace, Pierre-Simon},
journal = {M\'em. De Math. Et Phys. Pr\'esent\'es à l'Acad. Roy. Des Sci},
volume = {6},
@@ -168,21 +168,21 @@
}
@article{lecun1989optimal,
- title = {Optimal brain damage},
+ title = {Optimal Brain Damage},
author = {LeCun, Yann and Denker, John and Solla, Sara},
journal = nips,
year = {1989}
}
@book{mackay2003information,
- title = {Information theory, inference and learning algorithms},
+ title = {Information Theory, Inference and Learning Algorithms},
author = {MacKay, David},
year = {2003},
publisher = {Cambridge University Press}
}
@article{maddox2019simple,
- title = {A simple baseline for {B}ayesian uncertainty in deep learning},
+ title = {A Simple Baseline for {B}ayesian Uncertainty in Deep Learning},
author = {Maddox, Wesley J and Izmailov, Pavel and Garipov, Timur and Vetrov, Dmitry P and Wilson, Andrew Gordon},
journal = nips,
volume = {32},
@@ -190,14 +190,14 @@
}
@inproceedings{martens2015optimizing,
- title = {Optimizing neural networks with {K}ronecker-factored approximate curvature},
+ title = {Optimizing Neural Networks With {K}ronecker-Factored Approximate Curvature},
author = {Martens, James and Grosse, Roger},
booktitle = icml,
year = {2015}
}
@article{martens2020new,
- title = {New insights and perspectives on the natural gradient method},
+ title = {New Insights and Perspectives on the Natural Gradient Method},
author = {Martens, James},
journal = jmlr,
volume = {21},
@@ -214,28 +214,28 @@
}
@book{nocedal1999numerical,
- title = {Numerical optimization},
+ title = {Numerical Optimization},
author = {Nocedal, Jorge and Wright, Stephen J},
year = {1999},
publisher = {Springer}
}
@article{pascanu2013revisiting,
- title = {Revisiting natural gradient for deep networks},
+ title = {Revisiting Natural Gradient for Deep Networks},
author = {Pascanu, Razvan and Bengio, Yoshua},
journal = {arXiv preprint arXiv:1301.3584},
year = {2013}
}
@inproceedings{pleiss2020fast,
- title = {Fast matrix square roots with applications to {G}aussian processes and Bayesian optimization},
+ title = {Fast Matrix Square Roots With Applications to {G}aussian Processes and Bayesian Optimization},
author = {Pleiss, Geoff and Jankowiak, Martin and Eriksson, David and Damle, Anil and Gardner, Jacob},
booktitle = nips,
year = {2020}
}
@article{rattray1998natural,
- title = {Natural gradient descent for on-line learning},
+ title = {Natural Gradient Descent for on-Line Learning},
author = {Rattray, Magnus and Saad, David and Amari, Shun-ichi},
journal = {Physical review letters},
volume = {81},
@@ -246,7 +246,7 @@
}
@article{ritter2018online,
- title = {Online structured {L}aplace approximations for overcoming catastrophic forgetting},
+ title = {Online Structured {L}aplace Approximations for Overcoming Catastrophic Forgetting},
author = {Ritter, Hippolyt and Botev, Aleksandar and Barber, David},
journal = nips,
volume = {31},
@@ -254,7 +254,7 @@
}
@inproceedings{ritter2018scalable,
- title = {A scalable {L}aplace approximation for neural networks},
+ title = {A Scalable {L}aplace Approximation for Neural Networks},
author = {Ritter, Hippolyt and Botev, Aleksandar and Barber, David},
booktitle = iclr,
volume = {6},
@@ -268,14 +268,14 @@
}
@inproceedings{sutskever2013importance,
- title = {On the importance of initialization and momentum in deep learning},
+ title = {On the Importance of Initialization and Momentum in Deep Learning},
author = {Sutskever, Ilya and Martens, James and Dahl, George and Hinton, Geoffrey},
booktitle = icml,
year = {2013}
}
@article{vono2022high,
- title = {High-dimensional {G}aussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm},
+ title = {High-Dimensional {G}aussian Sampling: A Review and a Unifying Approach Based on a Stochastic Proximal Point Algorithm},
author = {Vono, Maxime and Dobigeon, Nicolas and Chainais, Pierre},
journal = {SIAM Review},
volume = {64},
@@ -286,14 +286,14 @@
}
@book{woodbury1950inverting,
- title = {Inverting modified matrices},
+ title = {Inverting Modified Matrices},
author = {Woodbury, Max},
year = {1950},
publisher = {Statistical Research Group}
}
@article{wu2019logan,
- title = {Logan: Latent optimisation for generative adversarial networks},
+ title = {Logan: Latent Optimisation for Generative Adversarial Networks},
author = {Wu, Yan and Donahue, Jeff and Balduzzi, David and Simonyan, Karen and Lillicrap, Timothy},
journal = {arXiv preprint arXiv:1912.00953},
year = {2019}
