Hezaveh, Yashar

10 publications

ICLR 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

ICLRW 2025 Solving Bayesian Inverse Problems with Diffusion Priors and Off-Policy RL Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Alexandre Adam, Yashar Hezaveh, Laurence Perreault-Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin

NeurIPSW 2024 Beyond Causal Discovery for Astronomy: Learning Meaningful Representations with Independent Component Analysis Zehao Jin, Mario Pasquato, Benjamin L. Davis, Andrea Maccio, Yashar Hezaveh

ICML 2024 Improving Gradient-Guided Nested Sampling for Posterior Inference Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault-Levasseur

ICMLW 2024 Inpainting Galaxy Counts onto N-Body Simulations over Multiple Cosmologies and Astrophysics Antoine Bourdin, Ronan Legin, Matthew Ho, Alexandre Adam, Yashar Hezaveh, Laurence Perreault-Levasseur

ICMLW 2024 Neural Ratio Estimators Meet Distributional Shift and Mode Misspecification: A Cautionary Tale from Strong Gravitational Lensing Andreas Filipp, Yashar Hezaveh, Laurence Perreault-Levasseur

ICLR 2024 On Diffusion Modeling for Anomaly Detection Victor Livernoche, Vineet Jain, Yashar Hezaveh, Siamak Ravanbakhsh

ICMLW 2024 Variable Star Light Curves in Koopman Space Mario Pasquato, Gaia Carenini, Nicolas Mekhaël, Vittorio F. Braga, Piero Trevisan, Giuseppe Bono, Yashar Hezaveh

ICML 2023 Sampling-Based Accuracy Testing of Posterior Estimators for General Inference Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault-Levasseur

NeurIPSW 2023 Score-Based Likelihood Characterization for Inverse Problems in the Presence of Non-Gaussian Noise Ronan Legin, Alexandre Adam, Yashar Hezaveh, Laurence Perreault-Levasseur