A Subset Approach to Contour Tracking in Clutter. - Daniel Freedman; Michael S. Brandstein (ICCV, 1999)

Provably Fast Algorithms for Contour Tracking. - Daniel Freedman; Michael S. Brandstein (CVPR, 2000)

Contour Tracking in Clutter: A Subset Approach. - Daniel Freedman; Michael S. Brandstein (Int. J. Comput. Vis., 2000)

Combinatorial curve reconstruction in Hilbert spaces: A new sampling theory and an old result revisited. - Daniel Freedman (Comput. Geom., 2002)

Efficient Simplicial Reconstructions of Manifolds from Their Samples. - Daniel Freedman (IEEE Trans. Pattern Anal. Mach. Intell., 2002)

Tracking Objects Using Density Matching and Shape Priors. - Tao Zhang; Daniel Freedman (ICCV, 2003)

Effective Tracking through Tree-Search. - Daniel Freedman (IEEE Trans. Pattern Anal. Mach. Intell., 2003)

Surface reconstruction, one triangle at a time. - Daniel Freedman (CCCG, 2004)

Model-Based Multi-Object Segmentation via Distribution Matching. - Daniel Freedman; Richard J. Radke; Tao Zhang; Yongwon Jeong; George T. Y. Chen (CVPR Workshops, 2004)

Active contours for tracking distributions. - Daniel Freedman; Tao Zhang (IEEE Trans. Image Process., 2004)

Energy Minimization via Graph Cuts: Settling What is Possible. - Daniel Freedman; Petros Drineas (CVPR (2), 2005)

Illumination-Invariant Tracking via Graph Cuts. - Daniel Freedman; Matthew W. Turek (CVPR (2), 2005)

Interactive Graph Cut Based Segmentation with Shape Priors. - Daniel Freedman; Tao Zhang (CVPR (1), 2005)

Improving Performance of Distribution Tracking through Background Mismatch. - Tao Zhang; Daniel Freedman (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

Model-based segmentation of medical imagery by matching distributions. - Daniel Freedman; Richard J. Radke; Tao Zhang; Yongwon Jeong; D. Michael Lovelock; George T. Y. Chen (IEEE Trans. Medical Imaging, 2005)

Multiscale Modeling and Constraints for Max-flow/Min-cut Problems in Computer Vision. - Matthew W. Turek; Daniel Freedman (CVPR Workshops, 2006)

An incremental algorithm for reconstruction of surfaces of arbitrary codimension. - Daniel Freedman (Comput. Geom., 2007)

Measuring and Localing Homology Classes - Daniel Freedman; Chao Chen 012 (CoRR, 2007)

Quantifying Homology Classes II: Localization and Stability - Chao Chen 012; Daniel Freedman (CoRR, 2007)

Quantifying Homology Classes. - Chao Chen 012; Daniel Freedman (STACS, 2008)

Fast Mean Shift by compact density representation. - Daniel Freedman; Pavel Kisilev (CVPR, 2009)

Fast Data Reduction via KDE Approximation. - Daniel Freedman; Pavel Kisilev (DCC, 2009)

Color Transforms for Creative Image Editing. - Pavel Kisilev; Daniel Freedman (CIC, 2009)

Parameter Tuning from Pairwise Preferences. - Pavel Kisilev; Daniel Freedman (BMVC, 2010)

Object-to-object color transfer: Optimal flows and SMSP transformations. - Daniel Freedman; Pavel Kisilev (CVPR, 2010)

Topology Noise Removal for Curve and Surface Evolution. - Chao Chen 012; Daniel Freedman (MCV, 2010)

Measuring and computing natural generators for homology groups. - Chao Chen 012; Daniel Freedman (Comput. Geom., 2010)

Graph cuts with many-pixel interactions: Theory and applications to shape modelling. - Daniel Freedman; Matthew W. Turek (Image Vis. Comput., 2010)

Computing Color Transforms with Applications to Image Editing. - Daniel Freedman; Pavel Kisilev (J. Math. Imaging Vis., 2010)

KDE Paring and a Faster Mean Shift Algorithm. - Daniel Freedman; Pavel Kisilev (SIAM J. Imaging Sci., 2010)

Enforcing topological constraints in random field image segmentation. - Chao Chen 012; Daniel Freedman; Christoph H. Lampert (CVPR, 2011)

Hardness Results for Homology Localization. - Chao Chen 012; Daniel Freedman (Discret. Comput. Geom., 2011)

Efficient and robust image descriptor for GUI object classification. - Anastasia Dubrovina; Pavel Kisilev; Daniel Freedman; Sagi Schein; Ruth Bergman (ICPR, 2012)

DFlow and DField: New features for capturing object and image relationships. - Pavel Kisilev; Daniel Freedman; Eugene Walach; Asaf Tzadok; Yehuda Naveh (ICPR, 2012)

An improved image graph for semi-automatic segmentation. - Daniel Freedman (Signal Image Video Process., 2012)

Discriminative Ferns Ensemble for Hand Pose Recognition. - Eyal Krupka; Alon Vinnikov; Ben Klein; Aharon Bar-Hillel; Daniel Freedman; Simon Stachniak (CVPR, 2014)

SRA: Fast Removal of General Multipath for ToF Sensors. - Daniel Freedman; Yoni Smolin; Eyal Krupka; Ido Leichter; Mirko Schmidt (ECCV (1), 2014)

Accurate, Robust, and Flexible Real-time Hand Tracking. - Toby Sharp; Cem Keskin; Duncan P. Robertson; Jonathan Taylor 001; Jamie Shotton; David Kim; Christoph Rhemann; Ido Leichter; Alon Vinnikov; Yichen Wei; Daniel Freedman; Pushmeet Kohli; et al. (CHI, 2015)

Reality Skins: Creating Immersive and Tactile Virtual Environments. - Lior Shapira; Daniel Freedman (ISMAR, 2016)

Toward Realistic Hands Gesture Interface: Keeping it Simple for Developers and Machines. - Eyal Krupka; Kfir Karmon; Noam Bloom; Daniel Freedman; Ilya Gurvich; Aviv Hurvitz; Ido Leichter; Yoni Smolin; Yuval Tzairi; Alon Vinnikov; Aharon Bar-Hillel (CHI, 2017)

ASIST: Automatic semantically invariant scene transformation. - Or Litany; Tal Remez; Daniel Freedman; Lior Shapira; Alexander M. Bronstein; Ran Gal (Comput. Vis. Image Underst., 2017)

SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels. - Or Litany; Daniel Freedman (CoRR, 2018)

Deep Energy: Using Energy Functions for Unsupervised Training of DNNs. - Alona Golts; Daniel Freedman; Michael Elad (CoRR, 2018)

Localization with Limited Annotation for Chest X-rays. - Eyal Rozenberg; Daniel Freedman; Alex M. Bronstein (ML4H@NeurIPS, 2019)

Localization with Limited Annotation. - Eyal Rozenberg; Daniel Freedman; Alexander M. Bronstein (CoRR, 2019)

Detecting muscle activation using ultrasound speed of sound inversion with deep learning. - Micha Feigin; Manuel Zwecker; Daniel Freedman; Brian W. Anthony (EMBC, 2020)

SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification. - Tomer Golany; Kira Radinsky; Daniel Freedman (ICML, 2020)

Learning an optimal PSF-pair for ultra-dense 3D localization microscopy. - Elias Nehme; Boris Ferdman; Lucien E. Weiss; Tal Naor; Daniel Freedman; Tomer Michaeli; Yoav Shechtman (CoRR, 2020)

A Deep Learning Framework for Single-Sided Sound Speed Inversion in Medical Ultrasound. - Micha Feigin; Daniel Freedman; Brian W. Anthony (IEEE Trans. Biomed. Eng., 2020)

Unsupervised Single Image Dehazing Using Dark Channel Prior Loss. - Alona Golts; Daniel Freedman; Michael Elad (IEEE Trans. Image Process., 2020)

Detecting Deficient Coverage in Colonoscopies. - Daniel Freedman; Yochai Blau; Liran Katzir 001; Amit Aides; Ilan Shimshoni; Danny Veikherman; Tomer Golany; Ariel Gordon; Greg Corrado; Yossi Matias; Ehud Rivlin (IEEE Trans. Medical Imaging, 2020)

ECG ODE-GAN: Learning Ordinary Differential Equations of ECG Dynamics via Generative Adversarial Learning. - Tomer Golany; Daniel Freedman; Kira Radinsky (AAAI, 2021)

Unsupervised 3D Shape Coverage Estimation with Applications to Colonoscopy. - Yochai Blau; Daniel Freedman; Valentin Dashinsky; Roman Goldenberg; Ehud Rivlin (ICCVW, 2021)

12-Lead ECG Reconstruction via Koopman Operators. - Tomer Golany; Kira Radinsky; Daniel Freedman; Saar Minha (ICML, 2021)

It Has Potential: Gradient-Driven Denoisers for Convergent Solutions to Inverse Problems. - Regev Cohen; Yochai Blau; Daniel Freedman; Ehud Rivlin (NeurIPS, 2021)

Learning to Localize Objects Using Limited Annotation, With Applications to Thoracic Diseases. - Eyal Rozenberg; Daniel Freedman; Alex M. Bronstein (IEEE Access, 2021)

Inverse Design of Quantum Holograms in Three-Dimensional Nonlinear Photonic Crystals. - Eyal Rozenberg; Aviv Karnieli; Ofir Yesharim; Sivan Trajtenberg-Mills; Daniel Freedman; Alex M. Bronstein; Ady Arie (CoRR, 2021)

SPDCinv: Inverse Quantum-Optical Design of High-Dimensional Qudits. - Eyal Rozenberg; Aviv Karnieli; Ofir Yesharim; Joshua Foley-Comer; Sivan Trajtenberg-Mills; Daniel Freedman; Alex M. Bronstein; Ady Arie (CoRR, 2021)

Deep Energy: Task Driven Training of Deep Neural Networks. - Alona Golts; Daniel Freedman; Michael Elad (IEEE J. Sel. Top. Signal Process., 2021)

Learning Optimal Wavefront Shaping for Multi-Channel Imaging. - Elias Nehme; Boris Ferdman; Lucien E. Weiss; Tal Naor; Daniel Freedman; Tomer Michaeli; Yoav Shechtman (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Estimating Withdrawal Time in Colonoscopies. - Liran Katzir 001; Danny Veikherman; Valentin Dashinsky; Roman Goldenberg; Ilan Shimshoni; Nadav Rabani; Regev Cohen; Ori Kelner; Ehud Rivlin; Daniel Freedman (ECCV Workshops (3), 2022)

Image Denoising with Deep Unfolding And Normalizing Flows. - Xinyi Wei; Hans Van Gorp; Lizeth Gonzalez-Carabarin; Daniel Freedman; Yonina C. Eldar; Ruud J. G. van Sloun (ICASSP, 2022)

Pixel-accurate Segmentation of Surgical Tools based on Bounding Box Annotations. - George Leifman; Amit Aides; Tomer Golany; Daniel Freedman; Ehud Rivlin (ICPR, 2022)

RepsNet: Combining Vision with Language for Automated Medical Reports. - Ajay Kumar Tanwani; Joelle K. Barral; Daniel Freedman (MICCAI (5), 2022)

Semi-Equivariant Continuous Normalizing Flows for Target-Aware Molecule Generation. - Eyal Rozenberg; Daniel Freedman (CoRR, 2022)

What's Behind the Mask: Estimating Uncertainty in Image-to-Image Problems. - Gilad Kutiel; Regev Cohen; Michael Elad; Daniel Freedman (CoRR, 2022)

Deep Unfolding With Normalizing Flow Priors for Inverse Problems. - Xinyi Wei; Hans Van Gorp; Lizeth Gonzalez-Carabarin; Daniel Freedman; Yonina C. Eldar; Ruud J. G. van Sloun (IEEE Trans. Signal Process., 2022)

Self-supervised Classification of Clinical Multivariate Time Series using Time Series Dynamics. - Yakir Yehuda; Daniel Freedman; Kira Radinsky (KDD, 2023)

Self-supervised Learning for Endoscopic Video Analysis. - Roy Hirsch; Mathilde Caron; Regev Cohen; Amir Livne; Ron Shapiro; Tomer Golany; Roman Goldenberg; Daniel Freedman; Ehud Rivlin (MICCAI (5), 2023)

Diffusion Models for Generative Histopathology. - Niranjan Sridhar; Michael Elad; Carson McNeil; Ehud Rivlin; Daniel Freedman (DGM4MICCAI, 2023)

Conformal Prediction Masks: Visualizing Uncertainty in Medical Imaging. - Gilad Kutiel; Regev Cohen; Michael Elad; Daniel Freedman; Ehud Rivlin (TML4H, 2023)

Semi-Equivariant Conditional Normalizing Flows. - Eyal Rozenberg; Daniel Freedman (CoRR, 2023)

Designing Nonlinear Photonic Crystals for High-Dimensional Quantum State Engineering. - Eyal Rozenberg; Aviv Karnieli; Ofir Yesharim; Joshua Foley-Comer; Sivan Trajtenberg-Mills; Sarika Mishra; Shashi Prabhakar; Ravindra Pratap Singh; Daniel Freedman; Alex M. Bronstein; Ady Arie (CoRR, 2023)

Weakly-Supervised Surgical Phase Recognition. - Roy Hirsch; Regev Cohen; Mathilde Caron; Tomer Golany; Daniel Freedman; Ehud Rivlin (CoRR, 2023)

Semi-equivariant conditional normalizing flows, with applications to target-aware molecule generation. - Eyal Rozenberg; Daniel Freedman (Mach. Learn. Sci. Technol., 2023)

On the Semantic Latent Space of Diffusion-Based Text-To-Speech Models. - Miri Varshavsky-Hassid; Roy Hirsch; Regev Cohen; Tomer Golany; Daniel Freedman; Ehud Rivlin (ACL (Short Papers), 2024)

Early Time Classification with Accumulated Accuracy Gap Control. - Liran Ringel; Regev Cohen; Daniel Freedman; Michael Elad; Yaniv Romano (ICML, 2024)

Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models. - Regev Cohen; Idan Kligvasser; Ehud Rivlin; Daniel Freedman (NeurIPS, 2024)

Random Walks for Temporal Action Segmentation with Timestamp Supervision. - Roy Hirsch; Regev Cohen; Tomer Golany; Daniel Freedman; Ehud Rivlin (WACV, 2024)

Overcoming Order in Autoregressive Graph Generation. - Edo Cohen-Karlik; Eyal Rozenberg; Daniel Freedman (CoRR, 2024)

A Theoretical Framework for an Efficient Normalizing Flow-Based Solution to the Schrodinger Equation. - Daniel Freedman; Eyal Rozenberg; Alex M. Bronstein (CoRR, 2024)

Molecular Diffusion Models with Virtual Receptors. - Matan Halfon; Eyal Rozenberg; Ehud Rivlin; Daniel Freedman (CoRR, 2024)

Streamlining Conformal Information Retrieval via Score Refinement. - Yotam Intrator; Ori Kelner; Regev Cohen; Roman Goldenberg; Ehud Rivlin; Daniel Freedman (CoRR, 2024)

ReHub: Linear Complexity Graph Transformers with Adaptive Hub-Spoke Reassignment. - Tomer Borreda; Daniel Freedman; Or Litany (CoRR, 2024)

HIPI: Spatially resolved multiplexed protein expression inferred from H&E WSIs. - Ron Zeira; Leon Anavy; Zohar Yakhini; Ehud Rivlin; Daniel Freedman (PLoS Comput. Biol., 2024)

Overcoming Order in Autoregressive Graph Generation for Molecule Generation. - Edo Cohen-Karlik; Eyal Rozenberg; Daniel Freedman (Trans. Mach. Learn. Res., 2024)

Computing Speed-of-Sound From Ultrasound: User-Agnostic Recovery and a New Benchmark. - Micha Feigin; Daniel Freedman; Brian W. Anthony (IEEE Trans. Biomed. Eng., 2024)

Principal Uncertainty Quantification With Spatial Correlation for Image Restoration Problems. - Omer Belhasin; Yaniv Romano; Daniel Freedman; Ehud Rivlin; Michael Elad (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

A Theoretical Framework for an Efficient Normalizing Flow-Based Solution to the Electronic Schrödinger Equation. - Daniel Freedman; Eyal Rozenberg; Alex M. Bronstein (AAAI, 2025)