Neuronal Regulation Implements Efficient Synaptic Pruning. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (NIPS, 1998)

Synaptic Pruning In Development: A Computational Account. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neural Comput., 1998)

Effective Learning Requires Neuronal Remodeling of Hebbian Synapses. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (NIPS, 1999)

Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neurocomputing, 1999)

Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neural Comput., 1999)

Temporally Dependent Plasticity: An Information Theoretic Account. - Gal Chechik; Naftali Tishby (NIPS, 2000)

Neuronal normalization provides effective learning through ineffective synaptic learning rules. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neurocomputing, 2000)

Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway. - Gal Chechik; Amir Globerson; Michael J. Anderson; Eric D. Young; Israel Nelken; Naftali Tishby (NIPS, 2001)

Spike timing dependent plasticity and mutual information in spiking neurons. - Gal Chechik (Neurocomputing, 2001)

Effective Neuronal Learning with Ineffective Hebbian Learning Rules. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neural Comput., 2001)

Extracting Relevant Structures with Side Information. - Gal Chechik; Naftali Tishby (NIPS, 2002)

Are There Representations in Embodied Evolved Agents? Taking Measures. - Hezi Avraham; Gal Chechik; Eytan Ruppin (ECAL, 2003)

Sufficient Dimensionality Reduction with Irrelevance Statistics. - Amir Globerson; Gal Chechik; Naftali Tishby (UAI, 2003)

Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization. - Gal Chechik (Neural Comput., 2003)

A needle in a haystack: local one-class optimization. - Koby Crammer; Gal Chechik (ICML, 2004)

Discrete profile alignment via constrained information bottleneck. - Sean O'Rourke; Gal Chechik; Robin Friedman; Eleazar Eskin (NIPS, 2004)

Encoding Stimulus Information by Spike Numbers and Mean Response Time in Primary Auditory Cortex. - Israel Nelken; Gal Chechik; Thomas D. Mrsic-Flogel; Andrew J. King; Jan W. H. Schnupp (J. Comput. Neurosci., 2005)

Information Bottleneck for Gaussian Variables. - Gal Chechik; Amir Globerson; Naftali Tishby; Yair Weiss (J. Mach. Learn. Res., 2005)

Embedding Heterogeneous Data Using Statistical Models. - Amir Globerson; Gal Chechik; Fernando Pereira 003; Naftali Tishby (AAAI, 2006)

Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks. - Alexis J. Battle; Gal Chechik; Daphne Koller (NIPS, 2006)

Max-margin classification of incomplete data. - Gal Chechik; Geremy Heitz; Gal Elidan; Pieter Abbeel; Daphne Koller (NIPS, 2006)

Discrete profile comparison using information bottleneck. - Sean O'Rourke; Gal Chechik; Robin Friedman; Eleazar Eskin (BMC Bioinform., 2006)

NIPS workshop on New Problems and Methods in Computational Biology. - Gal Chechik; Christina S. Leslie; William Stafford Noble; Gunnar Rätsch; Quaid Morris; Koji Tsuda (BMC Bioinform., 2007)

Euclidean Embedding of Co-occurrence Data. - Amir Globerson; Gal Chechik; Fernando Pereira 003; Naftali Tishby (J. Mach. Learn. Res., 2007)

Large-scale content-based audio retrieval from text queries. - Gal Chechik; Eugene Ie; Martin Rehn; Samy Bengio; Dick Lyon (Multimedia Information Retrieval, 2008)

Max-margin Classification of Data with Absent Features. - Gal Chechik; Geremy Heitz; Gal Elidan; Pieter Abbeel; Daphne Koller (J. Mach. Learn. Res., 2008)

An Online Algorithm for Large Scale Image Similarity Learning. - Gal Chechik; Uri Shalit; Varun Sharma; Samy Bengio (NIPS, 2009)

Timing of Gene Expression Responses to Environmental Changes. - Gal Chechik; Daphne Koller (J. Comput. Biol., 2009)

Object separation in x-ray image sets. - Geremy Heitz; Gal Chechik (CVPR, 2010)

Online Learning in The Manifold of Low-Rank Matrices. - Uri Shalit; Daphna Weinshall; Gal Chechik (NIPS, 2010)

Large Scale Online Learning of Image Similarity Through Ranking. - Gal Chechik; Varun Sharma; Uri Shalit; Samy Bengio (J. Mach. Learn. Res., 2010)

Sound Retrieval and Ranking Using Sparse Auditory Representations. - Richard F. Lyon; Martin Rehn; Samy Bengio; Thomas C. Walters; Gal Chechik (Neural Comput., 2010)

Sparse coding of auditory features for machine hearing in interference. - Richard F. Lyon; Jay Ponte; Gal Chechik (ICASSP, 2011)

Adaptive Regularization for Similarity Measures. - Koby Crammer; Gal Chechik (ICML, 2012)

Adaptive Regularization for Weight Matrices - Koby Crammer; Gal Chechik (CoRR, 2012)

Sufficient Dimensionality Reduction with Irrelevant Statistics - Amir Globerson; Gal Chechik; Naftali Tishby (CoRR, 2012)

Online Learning in the Embedded Manifold of Low-rank Matrices. - Uri Shalit; Daphna Weinshall; Gal Chechik (J. Mach. Learn. Res., 2012)

Localizing Genes to Cerebellar Layers by Classifying ISH Images. - Lior Kirsch; Noa Liscovitch; Gal Chechik (PLoS Comput. Biol., 2012)

Modeling Musical Influence with Topic Models. - Uri Shalit; Daphna Weinshall; Gal Chechik (ICML (2), 2013)

FuncISH: learning a functional representation of neural ISH images. - Noa Liscovitch; Uri Shalit; Gal Chechik (Bioinform., 2013)

Efficient coordinate-descent for orthogonal matrices through Givens rotations. - Uri Shalit; Gal Chechik (CoRR, 2013)

Specialization of Gene Expression during Mouse Brain Development. - Noa Liscovitch; Gal Chechik (PLoS Comput. Biol., 2013)

Coordinate-descent for learning orthogonal matrices through Givens rotations. - Uri Shalit; Gal Chechik (ICML, 2014)

Gradual training of deep denoising auto encoders. - Alexander Kalmanovich; Gal Chechik (CoRR, 2014)

Learning semantic representations of objects and their parts. - Grégoire Mesnil; Antoine Bordes; Jason Weston; Gal Chechik; Yoshua Bengio (Mach. Learn., 2014)

Probabilistic Graphical Models of Dyslexia. - Yair Lakretz; Gal Chechik; Naama Friedmann; Michal Rosen-Zvi (KDD, 2015)

Learning Sparse Metrics, One Feature at a Time. - Yuval Atzmon; Uri Shalit; Gal Chechik (FE@NIPS, 2015)

Gradual Training Method for Denoising Auto Encoders. - Alexander Kalmanovich; Gal Chechik (ICLR (Workshop), 2015)

Gene Expression Switching of Receptor Subunits in Human Brain Development. - Ossnat Bar-Shira; Ronnie Maor; Gal Chechik (PLoS Comput. Biol., 2015)

Learning to generalize to new compositions in image understanding. - Yuval Atzmon; Jonathan Berant; Vahid Kezami; Amir Globerson; Gal Chechik (CoRR, 2016)

On Expression Patterns and Developmental Origin of Human Brain Regions. - Lior Kirsch; Gal Chechik (PLoS Comput. Biol., 2016)

Context-Aware Captions from Context-Agnostic Supervision. - Ramakrishna Vedantam; Samy Bengio; Kevin Murphy 002; Devi Parikh; Gal Chechik (CVPR, 2017)

Learning from Noisy Large-Scale Datasets with Minimal Supervision. - Andreas Veit; Neil Alldrin; Gal Chechik; Ivan Krasin; Abhinav Gupta 001; Serge J. Belongie (CVPR, 2017)

DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders. - Ido Cohen 002; Eli (Omid) David; Nathan S. Netanyahu; Noa Liscovitch; Gal Chechik (ICANN (2), 2017)

Instance-Level Label Propagation with Multi-Instance Learning. - Qifan Wang 001; Gal Chechik; Chen Sun; Bin Shen 002 (IJCAI, 2017)

Group online adaptive learning. - Alon Zweig; Gal Chechik (Mach. Learn., 2017)

Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction. - Roei Herzig; Moshiko Raboh; Gal Chechik; Jonathan Berant; Amir Globerson (NeurIPS, 2018)

Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning. - Yuval Atzmon; Gal Chechik (UAI, 2018)

Metric Learning for Phoneme Perception. - Yair Lakretz; Gal Chechik; Evan-Gary Cohen; Alessandro Treves; Naama Friedmann (CoRR, 2018)

Domain-Aware Generalized Zero-Shot Learning. - Yuval Atzmon; Gal Chechik (CoRR, 2018)

Learning with Per-Sample Side Information. - Roman Visotsky; Yuval Atzmon; Gal Chechik (AGI, 2019)

Adaptive Confidence Smoothing for Generalized Zero-Shot Learning. - Yuval Atzmon; Gal Chechik (CVPR, 2019)

Informative Object Annotations: Tell Me Something I Don't Know. - Lior Bracha; Gal Chechik (CVPR, 2019)

Multilingual word translation using auxiliary languages. - Hagai Taitelbaum; Gal Chechik; Jacob Goldberger (EMNLP/IJCNLP (1), 2019)

A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation. - Hagai Taitelbaum; Gal Chechik; Jacob Goldberger (EMNLP/IJCNLP (1), 2019)

Network Adaptation Strategies for Learning New Classes without Forgetting the Original Ones. - Hagai Taitelbaum; Gal Chechik; Jacob Goldberger (ICASSP, 2019)

Joint Optimization for Cooperative Image Captioning. - Gilad Vered; Gal Oren 002; Yuval Atzmon; Gal Chechik (ICCV, 2019)

Deep Ranking-Based Sound Source Localization. - Renana Opochinsky; Bracha Laufer-Goldshtein; Sharon Gannot; Gal Chechik (WASPAA, 2019)

Learning Latent Scene-Graph Representations for Referring Relationships. - Moshiko Raboh; Roei Herzig; Gal Chechik; Jonathan Berant; Amir Globerson (CoRR, 2019)

Few-Shot Learning with Per-Sample Rich Supervision. - Roman Visotsky; Yuval Atzmon; Gal Chechik (CoRR, 2019)

Cooperative image captioning. - Gilad Vered; Gal Oren 002; Yuval Atzmon; Gal Chechik (CoRR, 2019)

Contrastive Learning for Weakly Supervised Phrase Grounding. - Tanmay Gupta; Arash Vahdat; Gal Chechik; Xiaodong Yang 001; Jan Kautz; Derek Hoiem (ECCV (3), 2020)

Learning Canonical Representations for Scene Graph to Image Generation. - Roei Herzig; Amir Bar; Huijuan Xu 001; Gal Chechik; Trevor Darrell; Amir Globerson (ECCV (26), 2020)

Learning Object Permanence from Video. - Aviv Shamsian; Ofri Kleinfeld; Amir Globerson; Gal Chechik (ECCV (16), 2020)

ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization. - Tzuf Paz-Argaman; Reut Tsarfaty; Gal Chechik; Yuval Atzmon (EMNLP (Findings), 2020)

On Learning Sets of Symmetric Elements. - Haggai Maron; Or Litany; Gal Chechik; Ethan Fetaya (ICML, 2020)

A causal view of compositional zero-shot recognition. - Yuval Atzmon; Felix Kreuk; Uri Shalit; Gal Chechik (NeurIPS, 2020)

Differentiable Scene Graphs. - Moshiko Raboh; Roei Herzig; Jonathan Berant; Gal Chechik; Amir Globerson (WACV, 2020)

Long-tail learning with attributes. - Dvir Samuel; Yuval Atzmon; Gal Chechik (CoRR, 2020)

Compositional Video Synthesis with Action Graphs. - Amir Bar; Roei Herzig; Xiaolong Wang 004; Gal Chechik; Trevor Darrell; Amir Globerson (CoRR, 2020)

Learning Object Detection from Captions via Textual Scene Attributes. - Achiya Jerbi; Roei Herzig; Jonathan Berant; Gal Chechik; Amir Globerson (CoRR, 2020)

How to Stop Epidemics: Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. - Eli A. Meirom; Haggai Maron; Shie Mannor; Gal Chechik (CoRR, 2020)

On Size Generalization in Graph Neural Networks. - Gilad Yehudai; Ethan Fetaya; Eli A. Meirom; Gal Chechik; Haggai Maron (CoRR, 2020)

Teacher-Student Consistency For Multi-Source Domain Adaptation. - Ohad Amosy; Gal Chechik (CoRR, 2020)

Deep Ranking-Based DOA Tracking Algorithm. - Renana Opochinsky; Gal Chechik; Sharon Gannot (EUSIPCO, 2021)

ACAV100M: Automatic Curation of Large-Scale Datasets for Audio-Visual Video Representation Learning. - Sangho Lee 008; Jiwan Chung; Youngjae Yu; Gunhee Kim; Thomas M. Breuel; Gal Chechik; Yale Song (ICCV, 2021)

Distributional Robustness Loss for Long-tail Learning. - Dvir Samuel; Gal Chechik (ICCV, 2021)

Auxiliary Learning by Implicit Differentiation. - Aviv Navon; Idan Achituve; Haggai Maron; Gal Chechik; Ethan Fetaya (ICLR, 2021)

Learning the Pareto Front with Hypernetworks. - Aviv Navon; Aviv Shamsian; Ethan Fetaya; Gal Chechik (ICLR, 2021)

GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. - Idan Achituve; Aviv Navon; Yochai Yemini; Gal Chechik; Ethan Fetaya (ICML, 2021)

Compositional Video Synthesis with Action Graphs. - Amir Bar; Roei Herzig; Xiaolong Wang 004; Anna Rohrbach; Gal Chechik; Trevor Darrell; Amir Globerson (ICML, 2021)

Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. - Eli A. Meirom; Haggai Maron; Shie Mannor; Gal Chechik (ICML, 2021)

Personalized Federated Learning using Hypernetworks. - Aviv Shamsian; Aviv Navon; Ethan Fetaya; Gal Chechik (ICML, 2021)

From Local Structures to Size Generalization in Graph Neural Networks. - Gilad Yehudai; Ethan Fetaya; Eli A. Meirom; Gal Chechik; Haggai Maron (ICML, 2021)

On Learning Sets of Symmetric Elements (Extended Abstract). - Haggai Maron; Or Litany; Gal Chechik; Ethan Fetaya (IJCAI, 2021)

Personalized Federated Learning With Gaussian Processes. - Idan Achituve; Aviv Shamsian; Aviv Navon; Gal Chechik; Ethan Fetaya (NeurIPS, 2021)

Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction. - Gal Dalal; Assaf Hallak; Steven Dalton; Iuri Frosio; Shie Mannor; Gal Chechik (NeurIPS, 2021)

Known unknowns: Learning novel concepts using reasoning-by-elimination. - Harsh Agrawal; Eli A. Meirom; Yuval Atzmon; Shie Mannor; Gal Chechik (UAI, 2021)

Self-Supervised Learning for Domain Adaptation on Point Clouds. - Idan Achituve; Haggai Maron; Gal Chechik (WACV, 2021)

From generalized zero-shot learning to long-tail with class descriptors. - Dvir Samuel; Yuval Atzmon; Gal Chechik (WACV, 2021)

Automatic Curation of Large-Scale Datasets for Audio-Visual Representation Learning. - Sangho Lee 008; Jiwan Chung; Youngjae Yu; Gunhee Kim; Thomas M. Breuel; Gal Chechik; Yale Song (CoRR, 2021)

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators. - Rinon Gal; Or Patashnik; Haggai Maron; Gal Chechik; Daniel Cohen-Or (CoRR, 2021)

Inference-Time Personalized Federated Learning. - Ohad Amosy; Gal Eyal; Gal Chechik (CoRR, 2021)

DETReg: Unsupervised Pretraining with Region Priors for Object Detection. - Amir Bar; Xin Wang 066; Vadim Kantorov; Colorado J. Reed; Roei Herzig; Gal Chechik; Anna Rohrbach; Trevor Darrell; Amir Globerson (CVPR, 2022)

Object-Region Video Transformers. - Roei Herzig; Elad Ben-Avraham; Karttikeya Mangalam; Amir Bar; Gal Chechik; Anna Rohrbach; Trevor Darrell; Amir Globerson (CVPR, 2022)

"This Is My Unicorn, Fluffy": Personalizing Frozen Vision-Language Representations. - Niv Cohen; Rinon Gal; Eli A. Meirom; Gal Chechik; Yuval Atzmon (ECCV (20), 2022)

On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. - Guy Tennenholtz; Assaf Hallak; Gal Dalal; Shie Mannor; Gal Chechik; Uri Shalit (ICLR, 2022)

Optimizing Tensor Network Contraction Using Reinforcement Learning. - Eli A. Meirom; Haggai Maron; Shie Mannor; Gal Chechik (ICML, 2022)

Multi-Task Learning as a Bargaining Game. - Aviv Navon; Aviv Shamsian; Idan Achituve; Haggai Maron; Kenji Kawaguchi; Gal Chechik; Ethan Fetaya (ICML, 2022)

Reinforcement Learning with a Terminator. - Guy Tennenholtz; Nadav Merlis; Lior Shani; Shie Mannor; Uri Shalit; Gal Chechik; Assaf Hallak; Gal Dalal (NeurIPS, 2022)

Coupled Training for Multi-Source Domain Adaptation. - Ohad Amosy; Gal Chechik (WACV, 2022)

Federated Learning with Heterogeneous Architectures using Graph HyperNetworks. - Or Litany; Haggai Maron; David Acuna; Jan Kautz; Gal Chechik; Sanja Fidler (CoRR, 2022)

Learning to reason about and to act on physical cascading events. - Yuval Atzmon; Eli A. Meirom; Shie Mannor; Gal Chechik (CoRR, 2022)

Example-based Hypernetworks for Out-of-Distribution Generalization. - Tomer Volk; Eyal Ben-David; Ohad Amosy; Gal Chechik; Roi Reichart (CoRR, 2022)

SoftTreeMax: Policy Gradient with Tree Search. - Gal Dalal; Assaf Hallak; Shie Mannor; Gal Chechik (CoRR, 2022)

Text2Model: Model Induction for Zero-shot Generalization Using Task Descriptions. - Ohad Amosy; Tomer Volk; Eyal Ben-David; Roi Reichart; Gal Chechik (CoRR, 2022)

Reinforcement Learning for Datacenter Congestion Control. - Chen Tessler; Yuval Shpigelman; Gal Dalal; Amit Mandelbaum; Doron Haritan Kazakov; Benjamin Fuhrer; Gal Chechik; Shie Mannor (SIGMETRICS Perform. Evaluation Rev., 2022)

StyleGAN-NADA: CLIP-guided domain adaptation of image generators. - Rinon Gal; Or Patashnik; Haggai Maron; Amit H. Bermano; Gal Chechik; Daniel Cohen-Or (ACM Trans. Graph., 2022)

Planning and Learning with Adaptive Lookahead. - Aviv Rosenberg 002; Assaf Hallak; Shie Mannor; Gal Chechik; Gal Dalal (AAAI, 2023)

DisCLIP: Open-Vocabulary Referring Expression Generation. - Lior Bracha; Eitan Shaar; Aviv Shamsian; Ethan Fetaya; Gal Chechik (BMVC, 2023)

Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs. - Benjamin Fuhrer; Yuval Shpigelman; Chen Tessler; Shie Mannor; Gal Chechik; Eitan Zahavi; Gal Dalal (CCGrid, 2023)

Example-based Hypernetworks for Multi-source Adaptation to Unseen Domains. - Tomer Volk; Eyal Ben-David; Ohad Amosy; Gal Chechik; Roi Reichart (EMNLP (Findings), 2023)

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion. - Rinon Gal; Yuval Alaluf; Yuval Atzmon; Or Patashnik; Amit Haim Bermano; Gal Chechik; Daniel Cohen-Or (ICLR, 2023)

Personalized Federated Learning for Medical Segmentation using Hypernetworks. - Hilit Segev; Gal Chechik (Tiny Papers @ ICLR, 2023)

Learning to Initiate and Reason in Event-Driven Cascading Processes. - Yuval Atzmon; Eli A. Meirom; Shie Mannor; Gal Chechik (ICML, 2023)

Graph Positional Encoding via Random Feature Propagation. - Moshe Eliasof; Fabrizio Frasca; Beatrice Bevilacqua; Eran Treister; Gal Chechik; Haggai Maron (ICML, 2023)

Equivariant Architectures for Learning in Deep Weight Spaces. - Aviv Navon; Aviv Shamsian; Idan Achituve; Ethan Fetaya; Gal Chechik; Haggai Maron (ICML, 2023)

Auxiliary Learning as an Asymmetric Bargaining Game. - Aviv Shamsian; Aviv Navon; Neta Glazer; Kenji Kawaguchi; Gal Chechik; Ethan Fetaya (ICML, 2023)

Train Hard, Fight Easy: Robust Meta Reinforcement Learning. - Ido Greenberg; Shie Mannor; Gal Chechik; Eli A. Meirom (NeurIPS, 2023)

Point Cloud Completion with Pretrained Text-to-Image Diffusion Models. - Yoni Kasten; Ohad Rahamim; Gal Chechik (NeurIPS, 2023)

Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment. - Royi Rassin; Eran Hirsch; Daniel Glickman; Shauli Ravfogel; Yoav Goldberg; Gal Chechik (NeurIPS, 2023)

Norm-guided latent space exploration for text-to-image generation. - Dvir Samuel; Rami Ben-Ari; Nir Darshan; Haggai Maron; Gal Chechik (NeurIPS, 2023)

CALM: Conditional Adversarial Latent Models for Directable Virtual Characters. - Chen Tessler; Yoni Kasten; Yunrong Guo; Shie Mannor; Gal Chechik; Xue Bin Peng (SIGGRAPH (Conference Paper Track), 2023)

Key-Locked Rank One Editing for Text-to-Image Personalization. - Yoad Tewel; Rinon Gal; Gal Chechik; Yuval Atzmon (SIGGRAPH (Conference Paper Track), 2023)

Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models. - Moab Arar; Rinon Gal; Yuval Atzmon; Gal Chechik; Daniel Cohen-Or; Ariel Shamir; Amit H. Bermano (SIGGRAPH Asia, 2023)

Guided Deep Kernel Learning. - Idan Achituve; Gal Chechik; Ethan Fetaya (UAI, 2023)

SoftTreeMax: Exponential Variance Reduction in Policy Gradient via Tree Search. - Gal Dalal; Assaf Hallak; Gugan Thoppe; Shie Mannor; Gal Chechik (CoRR, 2023)

Designing an Encoder for Fast Personalization of Text-to-Image Models. - Rinon Gal; Moab Arar; Yuval Atzmon; Amit H. Bermano; Gal Chechik; Daniel Cohen-Or (CoRR, 2023)

It is all about where you start: Text-to-image generation with seed selection. - Dvir Samuel; Rami Ben-Ari; Simon Raviv; Nir Darshan; Gal Chechik (CoRR, 2023)

Data Augmentations in Deep Weight Spaces. - Aviv Shamsian; David W. Zhang; Aviv Navon; Yan Zhang; Miltiadis Kofinas; Idan Achituve; Riccardo Valperga; Gertjan J. Burghouts; Efstratios Gavves; Cees G. M. Snoek; Ethan Fetaya; Gal Chechik; et al. (CoRR, 2023)

Fixed-point Inversion for Text-to-image diffusion models. - Barak Meiri; Dvir Samuel; Nir Darshan; Gal Chechik; Shai Avidan; Rami Ben-Ari (CoRR, 2023)

Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models. - Rinon Gal; Moab Arar; Yuval Atzmon; Amit H. Bermano; Gal Chechik; Daniel Cohen-Or (ACM Trans. Graph., 2023)

Generating Images of Rare Concepts Using Pre-trained Diffusion Models. - Dvir Samuel; Rami Ben-Ari; Simon Raviv; Nir Darshan; Gal Chechik (AAAI, 2024)

Breathing Life Into Sketches Using Text-to-Video Priors. - Rinon Gal; Yael Vinker; Yuval Alaluf; Amit Bermano; Daniel Cohen-Or; Ariel Shamir; Gal Chechik (CVPR, 2024)

LCM-Lookahead for Encoder-Based Text-to-Image Personalization. - Rinon Gal; Or Lichter; Elad Richardson; Or Patashnik; Amit H. Bermano; Gal Chechik; Daniel Cohen-Or (ECCV (14), 2024)

PlaMo: Plan and Move in Rich 3D Physical Environments. - Assaf Hallak; Gal Dalal; Chen Tessler; Kelly Guo; Shie Mannor; Gal Chechik (ECCV Workshops (2), 2024)

Text2Model: Text-based Model Induction for Zero-shot Image Classification. - Ohad Amosy; Tomer Volk; Eilam Shapira; Eyal Ben-David; Roi Reichart; Gal Chechik (EMNLP (Findings), 2024)

Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning. - Idan Achituve; Idit Diamant; Arnon Netzer; Gal Chechik; Ethan Fetaya (ICML, 2024)

Equivariant Deep Weight Space Alignment. - Aviv Navon; Aviv Shamsian; Ethan Fetaya; Gal Chechik; Nadav Dym; Haggai Maron (ICML, 2024)

Improved Generalization of Weight Space Networks via Augmentations. - Aviv Shamsian; Aviv Navon; David W. Zhang; Yan Zhang; Ethan Fetaya; Gal Chechik; Haggai Maron (ICML, 2024)

Where's Waldo: Diffusion Features For Personalized Segmentation and Retrieval. - Dvir Samuel; Rami Ben-Ari; Matan Levy; Nir Darshan; Gal Chechik (NeurIPS, 2024)

DiffUHaul: A Training-Free Method for Object Dragging in Images. - Omri Avrahami; Rinon Gal; Gal Chechik; Ohad Fried; Dani Lischinski; Arash Vahdat; Weili Nie (SIGGRAPH Asia, 2024)

Late to the party? On-demand unlabeled personalized federated learning. - Ohad Amosy; Gal Eyal; Gal Chechik (WACV, 2024)

Assessing Image Quality Using a Simple Generative Representation. - Simon Raviv; Gal Chechik (CoRR, 2024)

Unveiling the Power of Diffusion Features For Personalized Segmentation and Retrieval. - Dvir Samuel; Rami Ben-Ari; Matan Levy; Nir Darshan; Gal Chechik (CoRR, 2024)

Lay-A-Scene: Personalized 3D Object Arrangement Using Text-to-Image Priors. - Ohad Rahamim; Hilit Segev; Idan Achituve; Yuval Atzmon; Yoni Kasten; Gal Chechik (CoRR, 2024)

From Glucose Patterns to Health Outcomes: A Generalizable Foundation Model for Continuous Glucose Monitor Data Analysis. - Guy Lutsker; Gal Sapir; Anastasia Godneva; Smadar Shilo; Jerry R. Greenfield; Dorit Samocha-Bonet; Shie Mannor; Eli Meirom; Gal Chechik; Hagai Rossman; Eran Segal (CoRR, 2024)

ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation. - Rinon Gal; Adi Haviv; Yuval Alaluf; Amit H. Bermano; Daniel Cohen-Or; Gal Chechik (CoRR, 2024)

IT3: Idempotent Test-Time Training. - Nikita Durasov; Assaf Shocher; Doruk Öner; Gal Chechik; Alexei A. Efros; Pascal Fua (CoRR, 2024)

Multi-Shot Character Consistency for Text-to-Video Generation. - Yuval Atzmon; Rinon Gal; Yoad Tewel; Yoni Kasten; Gal Chechik (CoRR, 2024)

Bringing Objects to Life: 4D generation from 3D objects. - Ohad Rahamim; Ori Malca; Dvir Samuel; Gal Chechik (CoRR, 2024)

Training-Free Consistent Text-to-Image Generation. - Yoad Tewel; Omri Kaduri; Rinon Gal; Yoni Kasten; Lior Wolf; Gal Chechik; Yuval Atzmon (ACM Trans. Graph., 2024)

Iteration-Free quantum approximate optimization algorithm using neural networks. - Ohad Amosy; Tamuz Danzig; Ohad Lev; Ely Porat; Gal Chechik; Adi Makmal (Quantum Mach. Intell., 2024)

MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting. - Chen Tessler; Yunrong Guo; Ofir Nabati; Gal Chechik; Xue Bin Peng (ACM Trans. Graph., 2024)

Knowing Before Saying: LLM Representations Encode Information About Chain-of-Thought Success Before Completion. - Anum Afzal; Florian Matthes; Gal Chechik; Yftah Ziser (ACL (Findings), 2025)

Make It Count: Text-to-Image Generation with an Accurate Number of Objects. - Lital Binyamin; Yoad Tewel; Hilit Segev; Eran Hirsch; Royi Rassin; Gal Chechik (CVPR, 2025)

TriTex: Learning Texture from a Single Mesh via Triplane Semantic Features. - Dana Cohen-Bar; Daniel Cohen-Or; Gal Chechik; Yoni Kasten (CVPR, 2025)

RL-RC-DoT: A Block-level RL agent for Task-Aware Video Compression. - Uri Gadot; Assaf Shocher; Shie Mannor; Gal Chechik; Assaf Hallak (CVPR, 2025)

Adapting to the Unknown: Training-Free Audio-Visual Event Perception with Dynamic Thresholds. - Eitan Shaar; Ariel Shaulov; Gal Chechik; Lior Wolf (CVPR, 2025)

Classifier-Guided Captioning Across Modalities. - Ariel Shaulov; Tal Shaharabany; Eitan Shaar; Gal Chechik; Lior Wolf (ICASSP, 2025)

Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models. - Dvir Samuel; Barak Meiri; Haggai Maron; Yoad Tewel; Nir Darshan; Shai Avidan; Gal Chechik; Rami Ben-Ari (ICLR, 2025)

Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models. - Yoad Tewel; Rinon Gal; Dvir Samuel; Yuval Atzmon; Lior Wolf; Gal Chechik (ICLR, 2025)

Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models. - Michael Toker; Ido Galil; Hadas Orgad; Rinon Gal; Yoad Tewel; Gal Chechik; Yonatan Belinkov (NAACL (Long Papers), 2025)

Go Beyond Your Means: Unlearning with Per-Sample Gradient Orthogonalization. - Aviv Shamsian; Eitan Shaar; Aviv Navon; Gal Chechik; Ethan Fetaya (CoRR, 2025)

Learning on LLM Output Signatures for gray-box LLM Behavior Analysis. - Guy Bar-Shalom; Fabrizio Frasca; Derek Lim; Yoav Gelberg; Yftah Ziser; Ran El-Yaniv; Gal Chechik; Haggai Maron (CoRR, 2025)

Single Image Iterative Subject-driven Generation and Editing. - Yair Shpitzer; Gal Chechik; Idan Schwartz (CoRR, 2025)

OmnimatteZero: Training-free Real-time Omnimatte with Pre-trained Video Diffusion Models. - Dvir Samuel; Matan Levy; Nir Darshan; Gal Chechik; Rami Ben-Ari (CoRR, 2025)

Accelerating Vehicle Routing via AI-Initialized Genetic Algorithms. - Ido Greenberg; Piotr Sielski; Hugo Linsenmaier; Rajesh Gandham; Shie Mannor; Alexandre Fender; Gal Chechik; Eli A. Meirom (CoRR, 2025)

Efficient GNN Training Through Structure-Aware Randomized Mini-Batching. - Vignesh Balaji; Christos Kozyrakis; Gal Chechik; Haggai Maron (CoRR, 2025)

Emergent Active Perception and Dexterity of Simulated Humanoids from Visual Reinforcement Learning. - Zhengyi Luo 002; Chen Tessler; Toru Lin; Ye Yuan 007; Tairan He; Wenli Xiao; Yunrong Guo; Gal Chechik; Kris Kitani; Linxi Fan; Yuke Zhu (CoRR, 2025)

MaskedManipulator: Versatile Whole-Body Control for Loco-Manipulation. - Chen Tessler; Yifeng Jiang 009; Erwin Coumans; Zhengyi Luo 002; Gal Chechik; Xue Bin Peng (CoRR, 2025)

Policy Optimized Text-to-Image Pipeline Design. - Uri Gadot; Rinon Gal; Yftah Ziser; Gal Chechik; Shie Mannor (CoRR, 2025)

AblationBench: Evaluating Automated Planning of Ablations in Empirical AI Research. - Talor Abramovich; Gal Chechik (CoRR, 2025)

Per-Query Visual Concept Learning. - Ori Malca; Dvir Samuel; Gal Chechik (CoRR, 2025)