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ORCIDGal Chechik
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- affiliation: Stanford University, USA
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2020 – today
- 2024
[j30]Ohad Amosy, Tamuz Danzig, Ohad Lev, Ely Porat, Gal Chechik, Adi Makmal:
Iteration-Free quantum approximate optimization algorithm using neural networks. Quantum Mach. Intell. 6(2): 38 (2024)- [j29]Yoad Tewel
, Omri Kaduri, Rinon Gal, Yoni Kasten, Lior Wolf, Gal Chechik, Yuval Atzmon:
Training-Free Consistent Text-to-Image Generation. ACM Trans. Graph. 43(4): 52:1-52:18 (2024) - [j28]Chen Tessler, Yunrong Guo, Ofir Nabati, Gal Chechik, Xue Bin Peng:
MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting. ACM Trans. Graph. 43(6): 209:1-209:21 (2024) - [c99]Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, Gal Chechik:
Generating Images of Rare Concepts Using Pre-trained Diffusion Models. AAAI 2024: 4695-4703 - [c98]Rinon Gal, Yael Vinker, Yuval Alaluf, Amit Bermano, Daniel Cohen-Or, Ariel Shamir, Gal Chechik:
Breathing Life Into Sketches Using Text-to-Video Priors. CVPR 2024: 4325-4336 - [c97]Rinon Gal, Or Lichter, Elad Richardson, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
LCM-Lookahead for Encoder-Based Text-to-Image Personalization. ECCV (14) 2024: 322-340 - [c96]Ohad Amosy, Tomer Volk, Eilam Shapira, Eyal Ben-David, Roi Reichart, Gal Chechik:
Text2Model: Text-based Model Induction for Zero-shot Image Classification. EMNLP (Findings) 2024: 155-172 - [c95]Idan Achituve, Idit Diamant, Arnon Netzer, Gal Chechik, Ethan Fetaya:
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning. ICML 2024 - [c94]Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron:
Equivariant Deep Weight Space Alignment. ICML 2024 - [c93]Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron:
Improved Generalization of Weight Space Networks via Augmentations. ICML 2024 - [c92]Omri Avrahami, Rinon Gal, Gal Chechik, Ohad Fried, Dani Lischinski, Arash Vahdat, Weili Nie:
DiffUHaul: A Training-Free Method for Object Dragging in Images. SIGGRAPH Asia 2024: 38:1-38:12 - [c91]Ohad Amosy, Gal Eyal, Gal Chechik:
Late to the party? On-demand unlabeled personalized federated learning. WACV 2024: 2173-2182 - [i91]Yoad Tewel, Omri Kaduri, Rinon Gal, Yoni Kasten, Lior Wolf, Gal Chechik, Yuval Atzmon:
Training-Free Consistent Text-to-Image Generation. CoRR abs/2402.03286 (2024) - [i90]Idan Achituve, Idit Diamant, Arnon Netzer, Gal Chechik, Ethan Fetaya:
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning. CoRR abs/2402.04005 (2024) - [i89]Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron:
Improved Generalization of Weight Space Networks via Augmentations. CoRR abs/2402.04081 (2024) - [i88]Rinon Gal, Or Lichter, Elad Richardson, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
LCM-Lookahead for Encoder-based Text-to-Image Personalization. CoRR abs/2404.03620 (2024) - [i87]Simon Raviv, Gal Chechik:
Assessing Image Quality Using a Simple Generative Representation. CoRR abs/2404.18178 (2024) - [i86]Dvir Samuel, Rami Ben-Ari, Matan Levy, Nir Darshan, Gal Chechik:
Unveiling the Power of Diffusion Features For Personalized Segmentation and Retrieval. CoRR abs/2405.18025 (2024) - [i85]Ohad Rahamim, Hilit Segev, Idan Achituve, Yuval Atzmon, Yoni Kasten, Gal Chechik:
Lay-A-Scene: Personalized 3D Object Arrangement Using Text-to-Image Priors. CoRR abs/2406.00687 (2024) - [i84]Omri Avrahami, Rinon Gal, Gal Chechik, Ohad Fried, Dani Lischinski, Arash Vahdat, Weili Nie:
DiffUHaul: A Training-Free Method for Object Dragging in Images. CoRR abs/2406.01594 (2024) - [i83]Lital Binyamin, Yoad Tewel, Hilit Segev, Eran Hirsch, Royi Rassin, Gal Chechik:
Make It Count: Text-to-Image Generation with an Accurate Number of Objects. CoRR abs/2406.10210 (2024) - [i82]Assaf Hallak, Gal Dalal, Chen Tessler, Kelly Guo, Shie Mannor, Gal Chechik:
PlaMo: Plan and Move in Rich 3D Physical Environments. CoRR abs/2406.18237 (2024) - [i81]Guy Lutsker, Gal Sapir, Anastasia Godneva, Smadar Shilo, Jerry R. Greenfield, Dorit Samocha-Bonet, Shie Mannor, Eli Meirom, Gal Chechik, Hagai Rossman, Eran Segal:
From Glucose Patterns to Health Outcomes: A Generalizable Foundation Model for Continuous Glucose Monitor Data Analysis. CoRR abs/2408.11876 (2024) - [i80]Chen Tessler, Yunrong Guo, Ofir Nabati, Gal Chechik, Xue Bin Peng:
MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting. CoRR abs/2409.14393 (2024) - [i79]Rinon Gal, Adi Haviv, Yuval Alaluf, Amit H. Bermano, Daniel Cohen-Or, Gal Chechik:
ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation. CoRR abs/2410.01731 (2024) - [i78]Nikita Durasov, Assaf Shocher, Doruk Öner, Gal Chechik, Alexei A. Efros, Pascal Fua:
IT3: Idempotent Test-Time Training. CoRR abs/2410.04201 (2024) - [i77]Yoad Tewel, Rinon Gal, Dvir Samuel, Yuval Atzmon, Lior Wolf, Gal Chechik:
Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models. CoRR abs/2411.07232 (2024) - [i76]Yuval Atzmon, Rinon Gal, Yoad Tewel, Yoni Kasten, Gal Chechik:
Multi-Shot Character Consistency for Text-to-Video Generation. CoRR abs/2412.07750 (2024) - [i75]Ohad Rahamim, Ori Malca, Dvir Samuel, Gal Chechik:
Bringing Objects to Life: 4D generation from 3D objects. CoRR abs/2412.20422 (2024) - 2023
- [j27]Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models. ACM Trans. Graph. 42(4): 150:1-150:13 (2023) - [c90]Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal:
Planning and Learning with Adaptive Lookahead. AAAI 2023: 9606-9613 - [c89]Lior Bracha, Eitan Shaar, Aviv Shamsian, Ethan Fetaya, Gal Chechik:
DisCLIP: Open-Vocabulary Referring Expression Generation. BMVC 2023: 670-673 - [c88]Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal:
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs. CCGrid 2023: 331-343 - [c87]Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart:
Example-based Hypernetworks for Multi-source Adaptation to Unseen Domains. EMNLP (Findings) 2023: 9096-9113 - [c86]Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit Haim Bermano, Gal Chechik, Daniel Cohen-Or:
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion. ICLR 2023 - [c85]Hilit Segev, Gal Chechik:
Personalized Federated Learning for Medical Segmentation using Hypernetworks. Tiny Papers @ ICLR 2023 - [c84]Yuval Atzmon, Eli A. Meirom, Shie Mannor, Gal Chechik:
Learning to Initiate and Reason in Event-Driven Cascading Processes. ICML 2023: 1218-1243 - [c83]Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron:
Graph Positional Encoding via Random Feature Propagation. ICML 2023: 9202-9223 - [c82]Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron:
Equivariant Architectures for Learning in Deep Weight Spaces. ICML 2023: 25790-25816 - [c81]Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Auxiliary Learning as an Asymmetric Bargaining Game. ICML 2023: 30689-30705 - [c80]Ido Greenberg, Shie Mannor, Gal Chechik, Eli A. Meirom:
Train Hard, Fight Easy: Robust Meta Reinforcement Learning. NeurIPS 2023 - [c79]Yoni Kasten, Ohad Rahamim, Gal Chechik:
Point Cloud Completion with Pretrained Text-to-Image Diffusion Models. NeurIPS 2023 - [c78]Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik:
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment. NeurIPS 2023 - [c77]Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik:
Norm-guided latent space exploration for text-to-image generation. NeurIPS 2023 - [c76]Yoad Tewel, Rinon Gal, Gal Chechik, Yuval Atzmon:
Key-Locked Rank One Editing for Text-to-Image Personalization. SIGGRAPH (Conference Paper Track) 2023: 12:1-12:11 - [c75]Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng:
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters. SIGGRAPH (Conference Paper Track) 2023: 37:1-37:9 - [c74]Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik, Daniel Cohen-Or, Ariel Shamir, Amit H. Bermano:
Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models. SIGGRAPH Asia 2023: 72:1-72:10 - [c73]Idan Achituve, Gal Chechik, Ethan Fetaya:
Guided Deep Kernel Learning. UAI 2023: 11-21 - [i74]Ido Greenberg, Shie Mannor, Gal Chechik, Eli A. Meirom:
Train Hard, Fight Easy: Robust Meta Reinforcement Learning. CoRR abs/2301.11147 (2023) - [i73]Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron:
Equivariant Architectures for Learning in Deep Weight Spaces. CoRR abs/2301.12780 (2023) - [i72]Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik:
SoftTreeMax: Exponential Variance Reduction in Policy Gradient via Tree Search. CoRR abs/2301.13236 (2023) - [i71]Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Auxiliary Learning as an Asymmetric Bargaining Game. CoRR abs/2301.13501 (2023) - [i70]Idan Achituve, Gal Chechik, Ethan Fetaya:
Guided Deep Kernel Learning. CoRR abs/2302.09574 (2023) - [i69]Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
Designing an Encoder for Fast Personalization of Text-to-Image Models. CoRR abs/2302.12228 (2023) - [i68]Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron:
Graph Positional Encoding via Random Feature Propagation. CoRR abs/2303.02918 (2023) - [i67]Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, Gal Chechik:
It is all about where you start: Text-to-image generation with seed selection. CoRR abs/2304.14530 (2023) - [i66]Yoad Tewel, Rinon Gal, Gal Chechik, Yuval Atzmon:
Key-Locked Rank One Editing for Text-to-Image Personalization. CoRR abs/2305.01644 (2023) - [i65]Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng:
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters. CoRR abs/2305.02195 (2023) - [i64]Lior Bracha, Eitan Shaar, Aviv Shamsian, Ethan Fetaya, Gal Chechik:
DisCLIP: Open-Vocabulary Referring Expression Generation. CoRR abs/2305.19108 (2023) - [i63]Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik:
Norm-guided latent space exploration for text-to-image generation. CoRR abs/2306.08687 (2023) - [i62]Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik:
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment. CoRR abs/2306.08877 (2023) - [i61]Yoni Kasten, Ohad Rahamim, Gal Chechik:
Point-Cloud Completion with Pretrained Text-to-image Diffusion Models. CoRR abs/2306.10533 (2023) - [i60]Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik, Daniel Cohen-Or, Ariel Shamir, Amit H. Bermano:
Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models. CoRR abs/2307.06925 (2023) - [i59]Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron:
Equivariant Deep Weight Space Alignment. CoRR abs/2310.13397 (2023) - [i58]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, Haggai Maron:
Data Augmentations in Deep Weight Spaces. CoRR abs/2311.08851 (2023) - [i57]Rinon Gal, Yael Vinker, Yuval Alaluf, Amit H. Bermano, Daniel Cohen-Or, Ariel Shamir, Gal Chechik:
Breathing Life Into Sketches Using Text-to-Video Priors. CoRR abs/2311.13608 (2023) - [i56]Barak Meiri, Dvir Samuel, Nir Darshan, Gal Chechik, Shai Avidan, Rami Ben-Ari:
Fixed-point Inversion for Text-to-image diffusion models. CoRR abs/2312.12540 (2023) - 2022
- [j26]Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor:
Reinforcement Learning for Datacenter Congestion Control. SIGMETRICS Perform. Evaluation Rev. 49(2): 43-46 (2022) - [j25]Rinon Gal, Or Patashnik, Haggai Maron, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
StyleGAN-NADA: CLIP-guided domain adaptation of image generators. ACM Trans. Graph. 41(4): 141:1-141:13 (2022) - [c72]Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor:
Reinforcement Learning for Datacenter Congestion Control. AAAI 2022: 12615-12621 - [c71]Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam, Amir Bar, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson:
Object-Region Video Transformers. CVPR 2022: 3138-3149 - [c70]Amir Bar, Xin Wang, Vadim Kantorov, Colorado J. Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson:
DETReg: Unsupervised Pretraining with Region Priors for Object Detection. CVPR 2022: 14585-14595 - [c69]Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon:
"This Is My Unicorn, Fluffy": Personalizing Frozen Vision-Language Representations. ECCV (20) 2022: 558-577 - [c68]Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit:
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. ICLR 2022 - [c67]Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik:
Optimizing Tensor Network Contraction Using Reinforcement Learning. ICML 2022: 15278-15292 - [c66]Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Multi-Task Learning as a Bargaining Game. ICML 2022: 16428-16446 - [c65]Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal:
Reinforcement Learning with a Terminator. NeurIPS 2022 - [c64]Ohad Amosy, Gal Chechik:
Coupled Training for Multi-Source Domain Adaptation. WACV 2022: 1071-1080 - [i55]Or Litany, Haggai Maron, David Acuna, Jan Kautz, Gal Chechik, Sanja Fidler:
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks. CoRR abs/2201.08459 (2022) - [i54]Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal:
Planning and Learning with Adaptive Lookahead. CoRR abs/2201.12403 (2022) - [i53]Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Multi-Task Learning as a Bargaining Game. CoRR abs/2202.01017 (2022) - [i52]Yuval Atzmon, Eli A. Meirom, Shie Mannor, Gal Chechik:
Learning to reason about and to act on physical cascading events. CoRR abs/2202.01108 (2022) - [i51]Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart:
Example-based Hypernetworks for Out-of-Distribution Generalization. CoRR abs/2203.14276 (2022) - [i50]Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon:
"This is my unicorn, Fluffy": Personalizing frozen vision-language representations. CoRR abs/2204.01694 (2022) - [i49]Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik:
Optimizing Tensor Network Contraction Using Reinforcement Learning. CoRR abs/2204.09052 (2022) - [i48]Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal:
Reinforcement Learning with a Terminator. CoRR abs/2205.15376 (2022) - [i47]Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal:
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs. CoRR abs/2207.02295 (2022) - [i46]Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion. CoRR abs/2208.01618 (2022) - [i45]Gal Dalal, Assaf Hallak, Shie Mannor, Gal Chechik:
SoftTreeMax: Policy Gradient with Tree Search. CoRR abs/2209.13966 (2022) - [i44]Ohad Amosy, Tomer Volk, Eyal Ben-David, Roi Reichart, Gal Chechik:
Text2Model: Model Induction for Zero-shot Generalization Using Task Descriptions. CoRR abs/2210.15182 (2022) - 2021
- [c63]Renana Opochinsky, Gal Chechik, Sharon Gannot:
Deep Ranking-Based DOA Tracking Algorithm. EUSIPCO 2021: 1020-1024 - [c62]Dvir Samuel, Gal Chechik:
Distributional Robustness Loss for Long-tail Learning. ICCV 2021: 9475-9484 - [c61]Sangho Lee, Jiwan Chung, Youngjae Yu, Gunhee Kim, Thomas M. Breuel, Gal Chechik, Yale Song:
ACAV100M: Automatic Curation of Large-Scale Datasets for Audio-Visual Video Representation Learning. ICCV 2021: 10254-10264 - [c60]Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya:
Auxiliary Learning by Implicit Differentiation. ICLR 2021 - [c59]Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik:
Learning the Pareto Front with Hypernetworks. ICLR 2021 - [c58]Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya:
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. ICML 2021: 54-65 - [c57]Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson:
Compositional Video Synthesis with Action Graphs. ICML 2021: 662-673 - [c56]Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik:
Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. ICML 2021: 7565-7577 - [c55]Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik:
Personalized Federated Learning using Hypernetworks. ICML 2021: 9489-9502 - [c54]Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron:
From Local Structures to Size Generalization in Graph Neural Networks. ICML 2021: 11975-11986 - [c53]Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya:
On Learning Sets of Symmetric Elements (Extended Abstract). IJCAI 2021: 4794-4798 - [c52]Gal Dalal, Assaf Hallak, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik:
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction. NeurIPS 2021: 5518-5530 - [c51]Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya:
Personalized Federated Learning With Gaussian Processes. NeurIPS 2021: 8392-8406 - [c50]Harsh Agrawal, Eli A. Meirom, Yuval Atzmon, Shie Mannor, Gal Chechik:
Known unknowns: Learning novel concepts using reasoning-by-elimination. UAI 2021: 504-514 - [c49]Idan Achituve, Haggai Maron, Gal Chechik:
Self-Supervised Learning for Domain Adaptation on Point Clouds. WACV 2021: 123-133 - [c48]Dvir Samuel, Yuval Atzmon, Gal Chechik:
From generalized zero-shot learning to long-tail with class descriptors. WACV 2021: 286-295 - [i43]Sangho Lee, Jiwan Chung, Youngjae Yu, Gunhee Kim, Thomas M. Breuel, Gal Chechik, Yale Song:
Automatic Curation of Large-Scale Datasets for Audio-Visual Representation Learning. CoRR abs/2101.10803 (2021) - [i42]Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya:
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. CoRR abs/2102.07868 (2021) - [i41]Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor:
Reinforcement Learning for Datacenter Congestion Control. CoRR abs/2102.09337 (2021) - [i40]Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik:
Personalized Federated Learning using Hypernetworks. CoRR abs/2103.04628 (2021) - [i39]Dvir Samuel, Gal Chechik:
Distributional Robustness Loss for Long-tail Learning. CoRR abs/2104.03066 (2021) - [i38]Amir Bar, Xin Wang, Vadim Kantorov, Colorado J. Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson:
DETReg: Unsupervised Pretraining with Region Priors for Object Detection. CoRR abs/2106.04550 (2021) - [i37]Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya:
Personalized Federated Learning with Gaussian Processes. CoRR abs/2106.15482 (2021) - [i36]Assaf Hallak, Gal Dalal, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik:
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction. CoRR abs/2107.01715 (2021) - [i35]Rinon Gal, Or Patashnik, Haggai Maron, Gal Chechik, Daniel Cohen-Or:
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators. CoRR abs/2108.00946 (2021) - [i34]Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit:
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. CoRR abs/2110.06539 (2021) - [i33]Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam, Amir Bar, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson:
Object-Region Video Transformers. CoRR abs/2110.06915 (2021) - [i32]Ohad Amosy, Gal Eyal, Gal Chechik:
Inference-Time Personalized Federated Learning. CoRR abs/2111.08356 (2021) - 2020
- [c47]Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik:
Learning Object Permanence from Video. ECCV (16) 2020: 35-50 - [c46]Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson:
Learning Canonical Representations for Scene Graph to Image Generation. ECCV (26) 2020: 210-227 - [c45]Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem:
Contrastive Learning for Weakly Supervised Phrase Grounding. ECCV (3) 2020: 752-768 - [c44]Tzuf Paz-Argaman, Reut Tsarfaty, Gal Chechik, Yuval Atzmon:
ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization. EMNLP (Findings) 2020: 569-579 - [c43]Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya:
On Learning Sets of Symmetric Elements. ICML 2020: 6734-6744 - [c42]Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik:
A causal view of compositional zero-shot recognition. NeurIPS 2020 - [c41]Moshiko Raboh, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson:
Differentiable Scene Graphs. WACV 2020: 1477-1486 - [i31]Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya:
On Learning Sets of Symmetric Elements. CoRR abs/2002.08599 (2020) - [i30]Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik:
Learning Object Permanence from Video. CoRR abs/2003.10469 (2020) - [i29]Idan Achituve, Haggai Maron, Gal Chechik:
Self-Supervised Learning for Domain Adaptation on Point-Clouds. CoRR abs/2003.12641 (2020) - [i28]Dvir Samuel, Yuval Atzmon, Gal Chechik:
Long-tail learning with attributes. CoRR abs/2004.02235 (2020) - [i27]Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem:
Contrastive Learning for Weakly Supervised Phrase Grounding. CoRR abs/2006.09920 (2020) - [i26]Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik:
A causal view of compositional zero-shot recognition. CoRR abs/2006.14610 (2020) - [i25]Amir Bar, Roei Herzig, Xiaolong Wang, Gal Chechik, Trevor Darrell, Amir Globerson:
Compositional Video Synthesis with Action Graphs. CoRR abs/2006.15327 (2020) - [i24]Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya:
Auxiliary Learning by Implicit Differentiation. CoRR abs/2007.02693 (2020) - [i23]Achiya Jerbi, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson:
Learning Object Detection from Captions via Textual Scene Attributes. CoRR abs/2009.14558 (2020) - [i22]Tzuf Paz-Argaman, Yuval Atzmon, Gal Chechik, Reut Tsarfaty:
ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization. CoRR abs/2010.03276 (2020) - [i21]Aviv Navon, Aviv Shamsian, Gal Chechik, Ethan Fetaya:
Learning the Pareto Front with Hypernetworks. CoRR abs/2010.04104 (2020) - [i20]Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik:
How to Stop Epidemics: Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. CoRR abs/2010.05313 (2020) - [i19]Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron:
On Size Generalization in Graph Neural Networks. CoRR abs/2010.08853 (2020) - [i18]Ohad Amosy, Gal Chechik:
Teacher-Student Consistency For Multi-Source Domain Adaptation. CoRR abs/2010.10054 (2020)
2010 – 2019
- 2019
- [c40]Roman Visotsky, Yuval Atzmon, Gal Chechik:
Learning with Per-Sample Side Information. AGI 2019: 209-219 - [c39]Yuval Atzmon, Gal Chechik:
Adaptive Confidence Smoothing for Generalized Zero-Shot Learning. CVPR 2019: 11671-11680 - [c38]Lior Bracha, Gal Chechik:
Informative Object Annotations: Tell Me Something I Don't Know. CVPR 2019: 12507-12515 - [c37]Hagai Taitelbaum, Gal Chechik, Jacob Goldberger:
Multilingual word translation using auxiliary languages. EMNLP/IJCNLP (1) 2019: 1330-1335 - [c36]Hagai Taitelbaum, Gal Chechik, Jacob Goldberger:
A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation. EMNLP/IJCNLP (1) 2019: 3558-3563 - [c35]Hagai Taitelbaum, Gal Chechik, Jacob Goldberger:
Network Adaptation Strategies for Learning New Classes without Forgetting the Original Ones. ICASSP 2019: 3637-3641 - [c34]Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik:
Joint Optimization for Cooperative Image Captioning. ICCV 2019: 8897-8906 - [c33]Renana Opochinsky, Bracha Laufer-Goldshtein, Sharon Gannot, Gal Chechik:
Deep Ranking-Based Sound Source Localization. WASPAA 2019: 283-287 - [i17]Moshiko Raboh, Roei Herzig, Gal Chechik, Jonathan Berant, Amir Globerson:
Learning Latent Scene-Graph Representations for Referring Relationships. CoRR abs/1902.10200 (2019) - [i16]Roman Visotsky, Yuval Atzmon, Gal Chechik:
Few-Shot Learning with Per-Sample Rich Supervision. CoRR abs/1906.03859 (2019) - [i15]Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik:
Cooperative image captioning. CoRR abs/1907.11565 (2019) - [i14]Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson:
Learning Canonical Representations for Scene Graph to Image Generation. CoRR abs/1912.07414 (2019) - 2018
- [c32]Roei Herzig, Moshiko Raboh, Gal Chechik, Jonathan Berant, Amir Globerson:
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction. NeurIPS 2018: 7211-7221 - [c31]Yuval Atzmon, Gal Chechik:
Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning. UAI 2018: 382-392 - [i13]Roei Herzig, Moshiko Raboh, Gal Chechik, Jonathan Berant, Amir Globerson:
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction. CoRR abs/1802.05451 (2018) - [i12]Yuval Atzmon, Gal Chechik:
Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning. CoRR abs/1806.02664 (2018) - [i11]Yair Lakretz, Gal Chechik, Evan-Gary Cohen, Alessandro Treves, Naama Friedmann:
Metric Learning for Phoneme Perception. CoRR abs/1809.07824 (2018) - [i10]Yuval Atzmon, Gal Chechik:
Domain-Aware Generalized Zero-Shot Learning. CoRR abs/1812.09903 (2018) - [i9]Lior Bracha, Gal Chechik:
Informative Object Annotations: Tell Me Something I Don't Know. CoRR abs/1812.10358 (2018) - 2017
- [j24]Alon Zweig, Gal Chechik:
Group online adaptive learning. Mach. Learn. 106(9-10): 1747-1770 (2017) - [c30]Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik:
Context-Aware Captions from Context-Agnostic Supervision. CVPR 2017: 1070-1079 - [c29]Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge J. Belongie:
Learning from Noisy Large-Scale Datasets with Minimal Supervision. CVPR 2017: 6575-6583 - [c28]Ido Cohen, Eli (Omid) David, Nathan S. Netanyahu, Noa Liscovitch, Gal Chechik:
DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders. ICANN (2) 2017: 287-296 - [c27]Qifan Wang, Gal Chechik, Chen Sun, Bin Shen:
Instance-Level Label Propagation with Multi-Instance Learning. IJCAI 2017: 2943-2949 - [i8]Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge J. Belongie:
Learning From Noisy Large-Scale Datasets With Minimal Supervision. CoRR abs/1701.01619 (2017) - [i7]Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik:
Context-aware Captions from Context-agnostic Supervision. CoRR abs/1701.02870 (2017) - [i6]Ido Cohen, Eli David, Nathan S. Netanyahu, Noa Liscovitch, Gal Chechik:
DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders. CoRR abs/1711.09663 (2017) - 2016
- [j23]Lior Kirsch, Gal Chechik:
On Expression Patterns and Developmental Origin of Human Brain Regions. PLoS Comput. Biol. 12(8) (2016) - [i5]Yuval Atzmon, Jonathan Berant, Vahid Kezami, Amir Globerson, Gal Chechik:
Learning to generalize to new compositions in image understanding. CoRR abs/1608.07639 (2016) - 2015
- [j22]Ossnat Bar-Shira, Ronnie Maor, Gal Chechik:
Gene Expression Switching of Receptor Subunits in Human Brain Development. PLoS Comput. Biol. 11(12) (2015) - [c26]Yair Lakretz, Gal Chechik, Naama Friedmann, Michal Rosen-Zvi:
Probabilistic Graphical Models of Dyslexia. KDD 2015: 1919-1928 - [c25]Yuval Atzmon, Uri Shalit, Gal Chechik:
Learning Sparse Metrics, One Feature at a Time. FE@NIPS 2015: 30-48 - [c24]Alexander Kalmanovich, Gal Chechik:
Gradual Training Method for Denoising Auto Encoders. ICLR (Workshop) 2015 - 2014
- [j21]Grégoire Mesnil, Antoine Bordes, Jason Weston, Gal Chechik, Yoshua Bengio:
Learning semantic representations of objects and their parts. Mach. Learn. 94(2): 281-301 (2014) - [c23]Uri Shalit, Gal Chechik:
Coordinate-descent for learning orthogonal matrices through Givens rotations. ICML 2014: 548-556 - [i4]Alexander Kalmanovich, Gal Chechik:
Gradual training of deep denoising auto encoders. CoRR abs/1412.6257 (2014) - 2013
- [j20]Noa Liscovitch, Uri Shalit, Gal Chechik:
FuncISH: learning a functional representation of neural ISH images. Bioinform. 29(13): 36-43 (2013) - [j19]Noa Liscovitch, Gal Chechik:
Specialization of Gene Expression during Mouse Brain Development. PLoS Comput. Biol. 9(9) (2013) - [c22]Uri Shalit, Daphna Weinshall, Gal Chechik:
Modeling Musical Influence with Topic Models. ICML (2) 2013: 244-252 - [i3]Uri Shalit, Gal Chechik:
Efficient coordinate-descent for orthogonal matrices through Givens rotations. CoRR abs/1312.0624 (2013) - 2012
- [j18]Uri Shalit, Daphna Weinshall, Gal Chechik:
Online Learning in the Embedded Manifold of Low-rank Matrices. J. Mach. Learn. Res. 13: 429-458 (2012) - [j17]Lior Kirsch, Noa Liscovitch, Gal Chechik:
Localizing Genes to Cerebellar Layers by Classifying ISH Images. PLoS Comput. Biol. 8(12) (2012) - [c21]Koby Crammer, Gal Chechik:
Adaptive Regularization for Similarity Measures. ICML 2012 - [i2]Koby Crammer, Gal Chechik:
Adaptive Regularization for Weight Matrices. CoRR abs/1206.4639 (2012) - [i1]Amir Globerson, Gal Chechik, Naftali Tishby:
Sufficient Dimensionality Reduction with Irrelevant Statistics. CoRR abs/1212.2483 (2012) - 2011
- [c20]Richard F. Lyon, Jay Ponte, Gal Chechik:
Sparse coding of auditory features for machine hearing in interference. ICASSP 2011: 5876-5879 - 2010
- [j16]Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio:
Large Scale Online Learning of Image Similarity Through Ranking. J. Mach. Learn. Res. 11: 1109-1135 (2010) - [j15]Richard F. Lyon, Martin Rehn, Samy Bengio, Thomas C. Walters, Gal Chechik:
Sound Retrieval and Ranking Using Sparse Auditory Representations. Neural Comput. 22(9): 2390-2416 (2010) - [c19]Geremy Heitz, Gal Chechik:
Object separation in x-ray image sets. CVPR 2010: 2093-2100 - [c18]Uri Shalit, Daphna Weinshall, Gal Chechik:
Online Learning in The Manifold of Low-Rank Matrices. NIPS 2010: 2128-2136
2000 – 2009
- 2009
- [j14]Gal Chechik, Daphne Koller:
Timing of Gene Expression Responses to Environmental Changes. J. Comput. Biol. 16(2): 279-290 (2009) - [c17]Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio:
Large Scale Online Learning of Image Similarity through Ranking. IbPRIA 2009: 11-14 - [c16]Gal Chechik, Uri Shalit, Varun Sharma, Samy Bengio:
An Online Algorithm for Large Scale Image Similarity Learning. NIPS 2009: 306-314 - 2008
- [j13]Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller:
Max-margin Classification of Data with Absent Features. J. Mach. Learn. Res. 9: 1-21 (2008) - [c15]Gal Chechik, Eugene Ie, Martin Rehn, Samy Bengio, Dick Lyon:
Large-scale content-based audio retrieval from text queries. Multimedia Information Retrieval 2008: 105-112 - 2007
- [j12]Gal Chechik, Christina S. Leslie, William Stafford Noble, Gunnar Rätsch, Quaid Morris, Koji Tsuda:
NIPS workshop on New Problems and Methods in Computational Biology. BMC Bioinform. 8(S-10) (2007) - [j11]Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby:
Euclidean Embedding of Co-occurrence Data. J. Mach. Learn. Res. 8: 2265-2295 (2007) - 2006
- [j10]Sean O'Rourke, Gal Chechik, Robin Friedman, Eleazar Eskin:
Discrete profile comparison using information bottleneck. BMC Bioinform. 7(S-1) (2006) - [c14]Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby:
Embedding Heterogeneous Data Using Statistical Models. AAAI 2006: 1605-1608 - [c13]Alexis J. Battle, Gal Chechik, Daphne Koller:
Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks. NIPS 2006: 121-128 - [c12]Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller:
Max-margin classification of incomplete data. NIPS 2006: 233-240 - 2005
- [j9]Israel Nelken, Gal Chechik, Thomas D. Mrsic-Flogel, Andrew J. King, Jan W. H. Schnupp:
Encoding Stimulus Information by Spike Numbers and Mean Response Time in Primary Auditory Cortex. J. Comput. Neurosci. 19(2): 199-221 (2005) - [j8]Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss:
Information Bottleneck for Gaussian Variables. J. Mach. Learn. Res. 6: 165-188 (2005) - 2004
- [c11]Koby Crammer, Gal Chechik:
A needle in a haystack: local one-class optimization. ICML 2004 - [c10]Amir Globerson, Gal Chechik, Fernando C. N. Pereira, Naftali Tishby:
Euclidean Embedding of Co-Occurrence Data. NIPS 2004: 497-504 - [c9]Sean O'Rourke, Gal Chechik, Robin Friedman, Eleazar Eskin:
Discrete profile alignment via constrained information bottleneck. NIPS 2004: 1009-1016 - 2003
- [j7]Gal Chechik:
Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization. Neural Comput. 15(7): 1481-1510 (2003) - [c8]Hezi Avraham, Gal Chechik, Eytan Ruppin:
Are There Representations in Embodied Evolved Agents? Taking Measures. ECAL 2003: 743-752 - [c7]Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss:
Information Bottleneck for Gaussian Variables. NIPS 2003: 1213-1220 - [c6]Amir Globerson, Gal Chechik, Naftali Tishby:
Sufficient Dimensionality Reduction with Irrelevance Statistics. UAI 2003: 281-288 - 2002
- [c5]Gal Chechik, Naftali Tishby:
Extracting Relevant Structures with Side Information. NIPS 2002: 857-864 - 2001
- [j6]Gal Chechik:
Spike timing dependent plasticity and mutual information in spiking neurons. Neurocomputing 38-40: 147-152 (2001) - [j5]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Effective Neuronal Learning with Ineffective Hebbian Learning Rules. Neural Comput. 13(4): 817-840 (2001) - [c4]Gal Chechik, Amir Globerson, Michael J. Anderson, Eric D. Young, Israel Nelken, Naftali Tishby:
Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway. NIPS 2001: 173-180 - 2000
- [j4]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Neuronal normalization provides effective learning through ineffective synaptic learning rules. Neurocomputing 32-33: 345-351 (2000) - [c3]Gal Chechik, Naftali Tishby:
Temporally Dependent Plasticity: An Information Theoretic Account. NIPS 2000: 110-116
1990 – 1999
- 1999
- [j3]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development. Neurocomputing 26-27: 633-639 (1999) - [j2]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation. Neural Comput. 11(8): 2061-2080 (1999) - [c2]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Effective Learning Requires Neuronal Remodeling of Hebbian Synapses. NIPS 1999: 96-102 - 1998
- [j1]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Synaptic Pruning In Development: A Computational Account. Neural Comput. 10(7): 1759-1777 (1998) - [c1]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Neuronal Regulation Implements Efficient Synaptic Pruning. NIPS 1998: 97-103
Coauthor Index
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