Yashar Hezaveh

According to our database, Yashar Hezaveh authored at least 15 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

MIRA: A Score for Conditional Distribution Accuracy and Model Comparison.

Sammy Sharief, Justine Zeghal, Gabriel Missael Barco, Pablo Lemos, Yashar Hezaveh, Laurence Perreault Levasseur

CoRR, May, 2026

2025

Blind Strong Gravitational Lensing Inversion: Joint Inference of Source and Lens Mass with Score-Based Models.

Gabriel Missael Barco, Ronan Legin, Connor Stone, Yashar Hezaveh, Laurence Perreault Levasseur

CoRR, November, 2025

Solving Bayesian inverse problems with diffusion priors and off-policy RL.

Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yashar Hezaveh, Laurence Perreault Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin

CoRR, March, 2025

IRIS: A Bayesian Approach for Image Reconstruction in Radio Interferometry with expressive Score-Based priors.

Noe Dia, M. J. Yantovski-Barth, Alexandre Adam, Micah Bowles, Laurence Perreault Levasseur, Yashar Hezaveh, Anna M. M. Scaife

CoRR, January, 2025

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation.

Pablo Lemos, Sammy Nasser Sharief, Nikolay Malkin, Salma Salhi, Connor Stone, Laurence Perreault Levasseur, Yashar Hezaveh

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations.

Connor Stone, Alexandre Adam, Adam Coogan, M. J. Yantovski-Barth, Andreas Filipp, Landung Setiawan, Cordero Core, Ronan Legin, Charles Wilson, Gabriel Missael Barco, Yashar Hezaveh, Laurence Perreault Levasseur

J. Open Source Softw., December, 2024

Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems.

Gabriel Missael Barco, Alexandre Adam, Connor Stone, Yashar Hezaveh, Laurence Perreault Levasseur

CoRR, 2024

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation.

Pablo Lemos, Sammy Sharief, Nikolay Malkin, Laurence Perreault Levasseur, Yashar Hezaveh

CoRR, 2024

Improving Gradient-Guided Nested Sampling for Posterior Inference.

Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On Diffusion Modeling for Anomaly Detection.

Victor Livernoche, Vineet Jain, Yashar Hezaveh, Siamak Ravanbakhsh

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Bayesian Imaging for Radio Interferometry with Score-Based Priors.

Noe Dia, M. J. Yantovski-Barth, Alexandre Adam, Micah Bowles, Pablo Lemos, Anna M. M. Scaife, Yashar Hezaveh, Laurence Perreault Levasseur

CoRR, 2023

Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-Based Likelihoods and Priors.

Alexandre Adam, Connor Stone, Connor Bottrell, Ronan Legin, Yashar Hezaveh, Laurence Perreault Levasseur

CoRR, 2023

Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems using Recurrent Inference Machines.

Alexandre Adam, Laurence Perreault Levasseur, Yashar Hezaveh, Max Welling

CoRR, 2023

Sampling-Based Accuracy Testing of Posterior Estimators for General Inference.

Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault Levasseur

Proceedings of the International Conference on Machine Learning, 2023

2022

Posterior samples of source galaxies in strong gravitational lenses with score-based priors.

Alexandre Adam, Adam Coogan, Nikolay Malkin, Ronan Legin, Laurence Perreault Levasseur, Yashar Hezaveh, Yoshua Bengio

CoRR, 2022