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2020 – today
- 2022
[c15]Jonathan P. Lorraine, David Acuna, Paul Vicol, David Duvenaud:
Complex Momentum for Optimization in Games. AISTATS 2022: 7742-7765- [c14]Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster:
Lyapunov Exponents for Diversity in Differentiable Games. AAMAS 2022: 842-852 - [c13]Christina M. Funke, Paul Vicol, Kuan-Chieh Wang, Matthias Kümmerer, Richard S. Zemel, Matthias Bethge:
Disentanglement and Generalization Under Correlation Shifts. CoLLAs 2022: 116-141 - [c12]Paul Vicol, Jonathan P. Lorraine, Fabian Pedregosa, David Duvenaud, Roger B. Grosse:
On Implicit Bias in Overparameterized Bilevel Optimization. ICML 2022: 22234-22259 - [c11]Paul Vicol, Luke Metz, Jascha Sohl-Dickstein:
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies (Extended Abstract). IJCAI 2022: 5354-5358 - [i13]Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse:
Amortized Proximal Optimization. CoRR abs/2203.00089 (2022) - [i12]Paul Vicol, Jonathan Lorraine, Fabian Pedregosa, David Duvenaud, Roger B. Grosse:
On Implicit Bias in Overparameterized Bilevel Optimization. CoRR abs/2212.14032 (2022) - 2021
- [c10]Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger B. Grosse, Jörn-Henrik Jacobsen:
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks. AISTATS 2021: 1792-1800 - [c9]Paul Vicol, Luke Metz, Jascha Sohl-Dickstein:
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies. ICML 2021: 10553-10563 - [i11]Jonathan Lorraine
, David Acuna, Paul Vicol, David Duvenaud:
Complex Momentum for Learning in Games. CoRR abs/2102.08431 (2021) - [i10]Paul Vicol, Luke Metz, Jascha Sohl-Dickstein:
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies. CoRR abs/2112.13835 (2021) - [i9]Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster:
Lyapunov Exponents for Diversity in Differentiable Games. CoRR abs/2112.14570 (2021) - [i8]Christina M. Funke, Paul Vicol, Kuan-Chieh Wang, Matthias Kümmerer, Richard S. Zemel, Matthias Bethge:
Disentanglement and Generalization Under Correlation Shifts. CoRR abs/2112.14754 (2021) - 2020
- [c8]Jonathan Lorraine, Paul Vicol, David Duvenaud:
Optimizing Millions of Hyperparameters by Implicit Differentiation. AISTATS 2020: 1540-1552 - [i7]Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger B. Grosse, Jörn-Henrik Jacobsen:
Understanding and mitigating exploding inverses in invertible neural networks. CoRR abs/2006.09347 (2020)
2010 – 2019
- 2019
- [c7]Matthew MacKay, Paul Vicol, Jonathan Lorraine, David Duvenaud, Roger B. Grosse:
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions. ICLR (Poster) 2019 - [i6]Matthew MacKay, Paul Vicol, Jonathan Lorraine, David Duvenaud, Roger B. Grosse:
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions. CoRR abs/1903.03088 (2019) - [i5]Jonathan Lorraine, Paul Vicol, David Duvenaud:
Optimizing Millions of Hyperparameters by Implicit Differentiation. CoRR abs/1911.02590 (2019) - 2018
- [c6]Paul Vicol, Makarand Tapaswi, Lluís Castrejón, Sanja Fidler:
MovieGraphs: Towards Understanding Human-Centric Situations From Videos. CVPR 2018: 8581-8590 - [c5]Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse:
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. ICLR (Poster) 2018 - [c4]Kuan-Chieh Wang, Paul Vicol, James Lucas, Li Gu, Roger B. Grosse, Richard S. Zemel:
Adversarial Distillation of Bayesian Neural Network Posteriors. ICML 2018: 5177-5186 - [c3]Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B. Grosse:
Reversible Recurrent Neural Networks. NeurIPS 2018: 9043-9054 - [i4]Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse:
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. CoRR abs/1803.04386 (2018) - [i3]Kuan-Chieh Wang, Paul Vicol, James Lucas, Li Gu, Roger B. Grosse, Richard S. Zemel:
Adversarial Distillation of Bayesian Neural Network Posteriors. CoRR abs/1806.10317 (2018) - [i2]Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B. Grosse:
Reversible Recurrent Neural Networks. CoRR abs/1810.10999 (2018) - 2017
- [i1]Paul Vicol, Makarand Tapaswi, Lluís Castrejón, Sanja Fidler:
MovieGraphs: Towards Understanding Human-Centric Situations from Videos. CoRR abs/1712.06761 (2017) - 2016
- [c2]Paul Vicol, James P. Delgrande, Torsten Schaub:
A Minimization-Based Approach to Iterated Multi-Agent Belief Change. ECAI 2016: 1221-1229 - 2015
- [c1]Paul Vicol, James P. Delgrande, Torsten Schaub:
An Implementation of Consistency-Based Multi-agent Belief Change Using ASP. LPNMR 2015: 480-487
Coauthor Index
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last updated on 2023-02-19 00:00 CET by the dblp team
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