Adam M. Oberman

Orcid: 0000-0002-4214-7364

Affiliations:
  • McGill University


According to our database1, Adam M. Oberman authored at least 53 papers between 2003 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Multi-resolution continuous normalizing flows.
Ann. Math. Artif. Intell., October, 2024

2023
EuclidNets: An Alternative Operation for Efficient Inference of Deep Learning Models.
SN Comput. Sci., September, 2023

A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods.
Trans. Mach. Learn. Res., 2023

Addressing Sample Inefficiency in Multi-View Representation Learning.
CoRR, 2023

2022
Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models.
CoRR, 2022

EuclidNets: Combining Hardware and Architecture Design for Efficient Training and Inference.
Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods, 2022

FairCal: Fairness Calibration for Face Verification.
Proceedings of the Tenth International Conference on Learning Representations, 2022

On the Generalization of Representations in Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Stochastic Gradient Descent with Polyak's Learning Rate.
J. Sci. Comput., 2021

Improved Predictive Uncertainty using Corruption-based Calibration.
CoRR, 2021

Bias Mitigation of Face Recognition Models Through Calibration.
CoRR, 2021

2020
A Partial Differential Equation Obstacle Problem for the Level Set Approach to Visibility.
J. Sci. Comput., 2020

No-Collision Transportation Maps.
J. Sci. Comput., 2020

Adversarial Boot Camp: label free certified robustness in one epoch.
CoRR, 2020

Deterministic Gaussian Averaged Neural Networks.
CoRR, 2020

Learning normalizing flows from Entropy-Kantorovich potentials.
CoRR, 2020

How to train your neural ODE.
CoRR, 2020

How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization.
Proceedings of the 37th International Conference on Machine Learning, 2020

A principled approach for generating adversarial images under non-smooth dissimilarity metrics.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A Lyapunov analysis for accelerated gradient methods: from deterministic to stochastic case.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Partial differential equation regularization for supervised machine learning.
Proceedings of the 75 Years of Mathematics of Computation, 2020

2019
Improved Accuracy of Monotone Finite Difference Schemes on Point Clouds and Regular Grids.
SIAM J. Sci. Comput., 2019

Farkas layers: don't shift the data, fix the geometry.
CoRR, 2019

Partial differential equation regularization for supervised machine learning.
CoRR, 2019

Scaleable input gradient regularization for adversarial robustness.
CoRR, 2019

Empirical confidence estimates for classification by deep neural networks.
CoRR, 2019

The LogBarrier Adversarial Attack: Making Effective Use of Decision Boundary Information.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Anomaly Detection and Classification for Streaming Data using PDEs.
SIAM J. Appl. Math., 2018

Stochastic Backward Euler: An Implicit Gradient Descent Algorithm for k-Means Clustering.
J. Sci. Comput., 2018

Approximate Homogenization of Fully Nonlinear Elliptic PDEs: Estimates and Numerical Results for Pucci Type Equations.
J. Sci. Comput., 2018

Computing the Level Set Convex Hull.
J. Sci. Comput., 2018

Lipschitz regularized Deep Neural Networks converge and generalize.
CoRR, 2018

2017
A multigrid scheme for 3D Monge-Ampère equations.
Int. J. Comput. Math., 2017

Approximate Convex Hulls.
CoRR, 2017

Deep Relaxation: partial differential equations for optimizing deep neural networks.
CoRR, 2017

Partial differential equations for training deep neural networks.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016
Adaptive Finite Difference Methods for Nonlinear Elliptic and Parabolic Partial Differential Equations with Free Boundaries.
J. Sci. Comput., 2016

Anomaly detection and classification for streaming data using partial differential equations.
CoRR, 2016

2015
Filtered schemes for Hamilton-Jacobi equations: A simple construction of convergent accurate difference schemes.
J. Comput. Phys., 2015

2014
Numerical Methods for the Fractional Laplacian: A Finite Difference-Quadrature Approach.
SIAM J. Numer. Anal., 2014

Numerical solution of the Optimal Transportation problem using the Monge-Ampère equation.
J. Comput. Phys., 2014

A multigrid solver for the three dimensional Monge-Ampère equation.
CoRR, 2014

2013
A Numerical Method for Variational Problems with Convexity Constraints.
SIAM J. Sci. Comput., 2013

Convergent Filtered Schemes for the Monge-Ampère Partial Differential Equation.
SIAM J. Numer. Anal., 2013

Finite difference methods for the Infinity Laplace and <i>p</i>p-Laplace equations.
J. Comput. Appl. Math., 2013

2011
Convergent Finite Difference Solvers for Viscosity Solutions of the Elliptic Monge-Ampère Equation in Dimensions Two and Higher.
SIAM J. Numer. Anal., 2011

Fast finite difference solvers for singular solutions of the elliptic Monge-Ampère equation.
J. Comput. Phys., 2011

2009
Homogenization of Metric Hamilton-Jacobi Equations.
Multiscale Model. Simul., 2009

2006
Convergent Difference Schemes for Degenerate Elliptic and Parabolic Equations: Hamilton-Jacobi Equations and Free Boundary Problems.
SIAM J. Numer. Anal., 2006

2005
A convergent difference scheme for the infinity Laplacian: construction of absolutely minimizing Lipschitz extensions.
Math. Comput., 2005

2004
Computing the Effective Hamiltonian Using a Variational Approach.
SIAM J. Control. Optim., 2004

A convergent monotone difference scheme for motion of level sets by mean curvature.
Numerische Mathematik, 2004

2003
Pricing early exercise contracts in incomplete markets.
Comput. Manag. Sci., 2003


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