2 citations · 2 across the 5 of their papers we have counts for
6 papers
Composing and Steering Diffusion Models with Generalized Feynman-Kac Correctors
Wael Mattar, Daniel Freedman
Diffusion models have become the leading paradigm in generative modeling, yet many applications require sampling from distributions that are not those of any single pretrained mode…
Using Diffusion Models to Estimate Uncertainties in Analytic Continuation
Sagi Meir, Daniel Freedman, Barak Hirshberg
Inverse problems are ubiquitous in physics, chemistry, and engineering, arising when reconstructing hidden quantities from indirect measurements. A key example is the analytic cont…
Streamlining Conformal Information Retrieval via Score Refinement
Yotam Intrator, Ori Kelner, Regev Cohen +3
Information retrieval (IR) methods, like retrieval augmented generation, are fundamental to modern applications but often lack statistical guarantees. Conformal prediction addresse…
Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models
Regev Cohen, Idan Kligvasser, Ehud Rivlin +1
The pursuit of high perceptual quality in image restoration has driven the development of revolutionary generative models, capable of producing results often visually indistinguish…
On the Semantic Latent Space of Diffusion-Based Text-to-Speech Models
Miri Varshavsky-Hassid, Roy Hirsch, Regev Cohen +3
The incorporation of Denoising Diffusion Models (DDMs) in the Text-to-Speech (TTS) domain is rising, providing great value in synthesizing high quality speech. Although they exhibi…
Early Time Classification with Accumulated Accuracy Gap Control
Liran Ringel, Regev Cohen, Daniel Freedman +2
Early time classification algorithms aim to label a stream of features without processing the full input stream, while maintaining accuracy comparable to that achieved by applying…