3 citations · 4 across the 7 of their papers we have counts for
7 papers
Forget Narrowly, Retain Broadly: Unlearning as an Asymmetric Generalization Problem
Amit Peleg, Naman Deep Singh, Naama Pearl +2
Machine unlearning in LLMs is the targeted removal of specific knowledge while preserving all other capabilities, critical for privacy and safety. Yet existing benchmarks measure i…
Learn2Splat: Extending the Horizon of Learned 3DGS Optimization
Naama Pearl, Stefano Esposito, Haofei Xu +6
3D Gaussian Splatting (3DGS) optimization is most commonly performed using general-purpose first-order optimizers such as Adam or SGD. Although robust across scenes, they update ea…
Unimotion: Unifying 3D Human Motion Synthesis and Understanding
Chuqiao Li, Julian Chibane, Yannan He +3
We introduce Unimotion, the first unified multi-task human motion model capable of both flexible motion control and frame-level motion understanding. While existing works control a…
SVNR: Spatially-variant Noise Removal with Denoising Diffusion
Naama Pearl, Yaron Brodsky, Dana Berman +4
Denoising diffusion models have recently shown impressive results in generative tasks. By learning powerful priors from huge collections of training images, such models are able to…
SeaThru-NeRF: Neural Radiance Fields in Scattering Media
Deborah Levy, Amit Peleg, Naama Pearl +4
Research on neural radiance fields (NeRFs) for novel view generation is exploding with new models and extensions. However, a question that remains unanswered is what happens in und…
NAN: Noise-Aware NeRFs for Burst-Denoising
Naama Pearl, Tali Treibitz, Simon Korman
Burst denoising is now more relevant than ever, as computational photography helps overcome sensitivity issues inherent in mobile phones and small cameras. A major challenge in bur…
Metalearning Linear Bandits by Prior Update
Amit Peleg, Naama Pearl, Ron Meir
Fully Bayesian approaches to sequential decision-making assume that problem parameters are generated from a known prior. In practice, such information is often lacking. This proble…