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Laurence Perreault Levasseur
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Conference and Workshop Papers
- 2024
- [c3]Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur:
Improving Gradient-Guided Nested Sampling for Posterior Inference. ICML 2024 - 2023
- [c2]Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault Levasseur:
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference. ICML 2023: 19256-19273 - [c1]Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh:
Lie Point Symmetry and Physics-Informed Networks. NeurIPS 2023
Informal and Other Publications
- 2024
- [i12]Pablo Lemos, Sammy Sharief, Nikolay Malkin, Laurence Perreault Levasseur, Yashar Hezaveh:
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation. CoRR abs/2402.04355 (2024) - [i11]Gabriel Missael Barco, Alexandre Adam, Connor Stone, Yashar Hezaveh, Laurence Perreault Levasseur:
Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems. CoRR abs/2407.17667 (2024) - 2023
- [i10]Alexandre Adam, Laurence Perreault Levasseur, Yashar Hezaveh, Max Welling:
Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems using Recurrent Inference Machines. CoRR abs/2301.04168 (2023) - [i9]Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault Levasseur:
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference. CoRR abs/2302.03026 (2023) - [i8]Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh:
Lie Point Symmetry and Physics Informed Networks. CoRR abs/2311.04293 (2023) - [i7]Alexandre Adam, Connor Stone, Connor Bottrell, Ronan Legin, Yashar Hezaveh, Laurence Perreault Levasseur:
Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-Based Likelihoods and Priors. CoRR abs/2311.18002 (2023) - [i6]Noe Dia, M. J. Yantovski-Barth, Alexandre Adam, Micah Bowles, Pablo Lemos, Anna M. M. Scaife, Yashar Hezaveh, Laurence Perreault Levasseur:
Bayesian Imaging for Radio Interferometry with Score-Based Priors. CoRR abs/2311.18012 (2023) - [i5]Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur:
Improving Gradient-guided Nested Sampling for Posterior Inference. CoRR abs/2312.03911 (2023) - 2022
- [i4]Alexandre Adam, Adam Coogan, Nikolay Malkin, Ronan Legin, Laurence Perreault Levasseur, Yashar Hezaveh, Yoshua Bengio:
Posterior samples of source galaxies in strong gravitational lenses with score-based priors. CoRR abs/2211.03812 (2022) - 2020
- [i3]Tom Charnock, Laurence Perreault Levasseur, François Lanusse:
Bayesian Neural Networks. CoRR abs/2006.01490 (2020) - [i2]T. Lucas Makinen, Lachlan Lancaster, Francisco Villaescusa-Navarro, Peter Melchior, Shirley Ho, Laurence Perreault Levasseur, David N. Spergel:
deep21: a Deep Learning Method for 21cm Foreground Removal. CoRR abs/2010.15843 (2020) - 2019
- [i1]Juan Zamudio-Fernandez, Atakan Okan, Francisco Villaescusa-Navarro, Seda Bilaloglu, Asena Derin Cengiz, Siyu He, Laurence Perreault Levasseur, Shirley Ho:
HIGAN: Cosmic Neutral Hydrogen with Generative Adversarial Networks. CoRR abs/1904.12846 (2019)
Coauthor Index
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