Chechik, Gal

103 publications

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

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

ICLRW 2025 ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation Rinon Gal, Adi Haviv, Yuval Alaluf, Amit Haim Bermano, Daniel Cohen-Or, Gal Chechik

ICLRW 2025 GluFormer: Learning Generalizable Representations from Continuous Glucose Monitoring Data Guy Lutsker, Gal Sapir, Smadar Shilo, Jordi Merino, Anastasia Godneva, Jerry R Greenfield, Dorit Samocha-Bonet, Raja Dhir, Francisco Gude, Shie Mannor, Eli Meirom, Gal Chechik, Hagai Rossman, Eran Segal

ICML 2025 IT$^3$: Idempotent Test-Time Training Nikita Durasov, Assaf Shocher, Doruk Oner, Gal Chechik, Alexei A Efros, Pascal Fua

ICLRW 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

ICLR 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

CVPR 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

ICML 2025 Policy Gradient with Tree Expansion Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik

NeurIPS 2025 Policy Optimized Text-to-Image Pipeline Design Uri Gadot, Rinon Gal, Yftah Ziser, Gal Chechik, Shie Mannor

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 TriTex: Learning Texture from a Single Mesh via Triplane Semantic Features Dana Cohen-Bar, Daniel Cohen-Or, Gal Chechik, Yoni Kasten

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

CVPR 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

ICML 2024 Equivariant Deep Weight Space Alignment Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron

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

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

ECCV 2024 LCM-Lookahead for Encoder-Based Text-to-Image Personalization Rinon Gal, Or Lichter, Elad Richardson, Or Patashnik, Amit Bermano, Gal Chechik, Danny Cohen-Or

WACV 2024 Late to the Party? On-Demand Unlabeled Personalized Federated Learning Ohad Amosy, Gal Eyal, Gal Chechik

ECCVW 2024 PlaMo: Plan and Move in Rich 3D Physical Environments Assaf Hallak, Gal Dalal, Chen Tessler, Kelly Guo, Shie Mannor, Gal Chechik

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

ICLR 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

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

NeurIPSW 2023 Data Augmentations in Deep Weight Spaces Aviv Shamsian, David Zhang, Aviv Navon, Yan Zhang, Miltiadis Kofinas, Idan Achituve, Riccardo Valperga, Gertjan Burghouts, Efstratios Gavves, Cees Snoek, Ethan Fetaya, 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 Graph Positional Encoding via Random Feature Propagation Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

UAI 2023 Guided Deep Kernel Learning Idan Achituve, Gal Chechik, Ethan Fetaya

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

ICLRW 2023 Learning to Initiate and Reason in Event-Driven Cascading Processes Yuval Atzmon, Eli Meirom, Shie Mannor, 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

AAAI 2023 Planning and Learning with Adaptive Lookahead Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal

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

NeurIPS 2023 Train Hard, Fight Easy: Robust Meta Reinforcement Learning Ido Greenberg, Shie Mannor, Gal Chechik, Eli Meirom

WACV 2022 Coupled Training for Multi-Source Domain Adaptation Ohad Amosy, Gal Chechik

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

ICLRW 2022 Learning to Reason About and to Act on Physical Cascading Events Yuval Atzmon, Eli Meirom, 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

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

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

ICML 2022 Optimizing Tensor Network Contraction Using Reinforcement Learning Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik

AAAI 2022 Reinforcement Learning for Datacenter Congestion Control Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor

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

NeurIPSW 2022 SoftTreeMax: Policy Gradient with Tree Search Gal Dalal, Assaf Hallak, Shie Mannor, Gal Chechik

ECCV 2022 “This Is My Unicorn, Fluffy”: Personalizing Frozen Vision-Language Representations Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon

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

ICLR 2021 Auxiliary Learning by Implicit Differentiation Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya

ICML 2021 Compositional Video Synthesis with Action Graphs Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson

ICML 2021 Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik

NeurIPSW 2021 Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit

ICCV 2021 Distributional Robustness Loss for Long-Tail Learning Dvir Samuel, Gal Chechik

WACV 2021 From Generalized Zero-Shot Learning to Long-Tail with Class Descriptors Dvir Samuel, Yuval Atzmon, Gal Chechik

ICML 2021 From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai, Ethan Fetaya, Eli Meirom, Gal Chechik, Haggai Maron

ICML 2021 GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning Idan Achituve, Aviv Navon, Yochai Yemini, 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

UAI 2021 Known Unknowns: Learning Novel Concepts Using Reasoning-by-Elimination Harsh Agrawal, Eli A. Meirom, Yuval Atzmon, Shie Mannor, Gal Chechik

ICLR 2021 Learning the Pareto Front with Hypernetworks Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik

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

ICML 2021 Personalized Federated Learning Using Hypernetworks Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik

NeurIPS 2021 Personalized Federated Learning with Gaussian Processes Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya

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

NeurIPS 2020 A Causal View of Compositional Zero-Shot Recognition Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik

ECCV 2020 Contrastive Learning for Weakly Supervised Phrase Grounding Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem

WACV 2020 Differentiable Scene Graphs Moshiko Raboh, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson

ECCV 2020 Learning Canonical Representations for Scene Graph to Image Generation Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson

ECCV 2020 Learning Object Permanence from Video Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik

ICML 2020 On Learning Sets of Symmetric Elements Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

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

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

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

MLJ 2017 Group Online Adaptive Learning Alon Zweig, Gal Chechik

IJCAI 2017 Instance-Level Label Propagation with Multi-Instance Learning Qifan Wang, Gal Chechik, Chen Sun, Bin Shen

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

ICLR 2015 Gradual Training Method for Denoising Auto Encoders Alexander Kalmanovich, Gal Chechik

ICML 2014 Coordinate-Descent for Learning Orthogonal Matrices Through Givens Rotations Uri Shalit, Gal Chechik

MLJ 2014 Learning Semantic Representations of Objects and Their Parts Grégoire Mesnil, Antoine Bordes, Jason Weston, Gal Chechik, Yoshua Bengio

ICML 2013 Modeling Musical Influence with Topic Models Uri Shalit, Daphna Weinshall, Gal Chechik

ICML 2012 Adaptive Regularization for Similarity Measures Koby Crammer, Gal Chechik

JMLR 2012 Online Learning in the Embedded Manifold of Low-Rank Matrices Uri Shalit, Daphna Weinshall, Gal Chechik

JMLR 2010 Large Scale Online Learning of Image Similarity Through Ranking Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio

CVPR 2010 Object Separation in X-Ray Image Sets Geremy Heitz, Gal Chechik

NeurIPS 2010 Online Learning in the Manifold of Low-Rank Matrices Uri Shalit, Daphna Weinshall, Gal Chechik

NeurIPS 2009 An Online Algorithm for Large Scale Image Similarity Learning Gal Chechik, Uri Shalit, Varun Sharma, Samy Bengio

JMLR 2008 Max-Margin Classification of Data with Absent Features Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

JMLR 2007 Euclidean Embedding of Co-Occurrence Data Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby

AAAI 2006 Embedding Heterogeneous Data Using Statistical Models Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby

NeurIPS 2006 Max-Margin Classification of Incomplete Data Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

NeurIPS 2006 Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks Alexis Battle, Gal Chechik, Daphne Koller

JMLR 2005 Information Bottleneck for Gaussian Variables Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss

ICML 2004 A Needle in a Haystack: Local One-Class Optimization Koby Crammer, Gal Chechik

NeurIPS 2004 Discrete Profile Alignment via Constrained Information Bottleneck Sean O'rourke, Gal Chechik, Robin Friedman, Eleazar Eskin

NeurIPS 2004 Euclidean Embedding of Co-Occurrence Data Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby

NeurIPS 2003 Information Bottleneck for Gaussian Variables Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss

NeCo 2003 Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization Gal Chechik

UAI 2003 Sufficient Dimensionality Reduction with Irrelevance Statistics Amir Globerson, Gal Chechik, Naftali Tishby

NeurIPS 2002 Extracting Relevant Structures with Side Information Gal Chechik, Naftali Tishby

NeCo 2001 Effective Neuronal Learning with Ineffective Hebbian Learning Rules Gal Chechik, Isaac Meilijson, Eytan Ruppin

NeurIPS 2001 Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway Gal Chechik, Amir Globerson, M. J. Anderson, E. D. Young, Israel Nelken, Naftali Tishby

NeurIPS 2000 Temporally Dependent Plasticity: An Information Theoretic Account Gal Chechik, Naftali Tishby

NeurIPS 1999 Effective Learning Requires Neuronal Remodeling of Hebbian Synapses Gal Chechik, Isaac Meilijson, Eytan Ruppin

NeCo 1999 Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation Gal Chechik, Isaac Meilijson, Eytan Ruppin

NeurIPS 1998 Neuronal Regulation Implements Efficient Synaptic Pruning Gal Chechik, Isaac Meilijson, Eytan Ruppin

NeCo 1998 Synaptic Pruning in Development: A Computational Account Gal Chechik, Isaac Meilijson, Eytan Ruppin