Publications
You can also find many of my publications on my dblp profile and my Google Scholar profile.
Year of Publication
2021
Finlay, Chris, and Adam M. Oberman:
Scaleable input gradient regularization for adversarial robustness
Machine Learning with Applications [doi] [arXiv] [GitHub]
2020
Finlay, Chris, Jörn-Henrik Jacobsen, Levon Nurbekyan, and Adam M. Oberman:
How to train your Neural ODE: the world of Jacobian and kinetic regularization
International Conference on Machine Learning (ICML) [arXiv] [GitHub]Aram-Alexandre Pooladian, Chris Finlay, Tim Hoheisel, and Adam M. Oberman:
A principled approach for generating adversarial images under non-smooth dissimilarity metrics
Artificial Intelligence and Statistics (AISTATS) [arXiv] [GitHub]
2019
Finlay, Chris, Aram-Alexandre Pooladian and Adam M. Oberman:
The LogBarrier adversarial attack: making effective use of decision boundary information
International Conference on Computer Vision (ICCV) [arXiv] [GitHub]Finlay, Chris, and Adam M. Oberman:
Improved accuracy of monotone finite difference schemes on point clouds and regular grids
SIAM Journal on Scientific Computing (SISC) [doi] [arXiv] [GitHub]
2018
Finlay, Chris, and Adam M. Oberman:
Approximate homogenization of convex nonlinear elliptic PDEs
Communications in Mathematical Sciences [doi] [arXiv]Finlay, Chris, and Adam M. Oberman:
Approximate homogenization of fully nonlinear elliptic PDEs: estimates and results for Pucci type equations
Journal of Scientific Computing [doi] [arXiv]
2015
Sattler, Derek F., Chris Finlay, and James D. Stewart.:
Annual ring density for lodgepole pine as derived from models for earlywood density, latewood density and latewood proportion
Forestry: An International Journal of Forest Research [doi]
2013
Gong, Jiafen, Mairon M. Dos Santos, Chris Finlay, and Thomas Hillen:
Are more complicated tumour control probability models better?
Mathematical Medicine and Biology [doi]
2010
Hillen, Thomas, Gerda De VrieS, Jiafen Gong, and Chris Finlay:
From cell population models to tumor control probability: including cell cycle effects
Acta Oncologica [doi]
preprints and workshops
Finlay, Chris, Augusto Gerolin, Adam M. Oberman, and Aram-Alexandre Pooladian:
Learning normalizing flows from Entropy-Kantorovich potentials
ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (Contributed talk) [arXiv]
Campbell, Ryan, Chris Finlay, and Adam M. Oberman:
Deterministic Gaussian Averaged Neural Networks
[arXiv] [GitHub]
Finlay, Chris, Jeff Calder, Bilal Abbasi, and Adam M. Oberman:
Lipschitz regularized deep neural networks generalize and are adversarially robust
[arXiv]