Michael Arbel

According to our database1, Michael Arbel authored at least 21 papers between 2017 and 2022.

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Bibliography

2022
Continual Repeated Annealed Flow Transport Monte Carlo.
Proceedings of the International Conference on Machine Learning, 2022

Towards an Understanding of Default Policies in Multitask Policy Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Amortized Implicit Differentiation for Stochastic Bilevel Optimization.
CoRR, 2021

Deep Reinforcement Learning with Dynamic Optimism.
CoRR, 2021

Tactical Optimism and Pessimism for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Annealed Flow Transport Monte Carlo.
Proceedings of the 38th International Conference on Machine Learning, 2021

The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods.
Proceedings of the 9th International Conference on Learning Representations, 2021

Efficient Wasserstein Natural Gradients for Reinforcement Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Generalized Energy Based Models.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Estimating Barycenters of Measures in High Dimensions.
CoRR, 2020

KALE: When Energy-Based Learning Meets Adversarial Training.
CoRR, 2020

A Non-Asymptotic Analysis for Stein Variational Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Kernelized Wasserstein Natural Gradient.
Proceedings of the 8th International Conference on Learning Representations, 2020

Synchronizing Probability Measures on Rotations via Optimal Transport.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Maximum Mean Discrepancy Gradient Flow.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
On gradient regularizers for MMD GANs.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Demystifying MMD GANs.
Proceedings of the 6th International Conference on Learning Representations, 2018

Efficient and principled score estimation with Nyström kernel exponential families.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Kernel Conditional Exponential Family.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Efficient and principled score estimation.
CoRR, 2017


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