From the 1 of 16 linked papers with an AI index.
1 citations · 1 across the 5 of their papers we have counts for
16 papers
Efficient Conformal Prediction for Regression Models under Label Noise
Yahav Cohen, Jacob Goldberger, Tom Tirer
The paper introduces a method to apply conformal prediction to regression models when the calibration data have noisy labels, by estimating a noise‑free threshold and providing a p…
Jacobian-Aware Posterior Sampling for Inverse Problems
Liav Hen, Tom Tirer, Raja Giryes +1
Diffusion models provide powerful generative priors for solving inverse problems by sampling from a posterior distribution conditioned on corrupted measurements. Existing methods p…
Does the Data Processing Inequality Reflect Practice? On the Utility of Low-Level Tasks
Roy Turgeman, Tom Tirer
The data processing inequality is an information-theoretic principle stating that the information content of a signal cannot be increased by processing the observations. In particu…
Enhancing Conformal Prediction via Class Similarity
Ariel Fargion, Lahav Dabah, Tom Tirer
Conformal Prediction (CP) has emerged as a powerful statistical framework for high-stakes classification applications. Instead of predicting a single class, CP generates a predicti…
Reducing Diffusion Model Memorization with Higher Order Langevin Dynamics
Benjamin Sterling, Mónica F. Bugallo, Tom Tirer
Diffusion/score-based models have emerged as powerful generative models, capable of generating high-quality samples that mimic the training data distribution. However, it has been…
Image-Adaptive GAN based Reconstruction
Shady Abu Hussein, Tom Tirer, Raja Giryes
In the recent years, there has been a significant improvement in the quality of samples produced by (deep) generative models such as variational auto-encoders and generative advers…