Yerlan Idelbayev

27 papers A* 8A 1B 3Misc 2Journal 10Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
SnapGen++: Unleashing Diffusion Transformers for Efficient High-Fidelity Image Generation on Edge Devices.
CoRR
Dongting Hu, Aarush Gupta, Magzhan Gabidolla, Arpit Sahni, Huseyin Coskun, Yanyu Li, Yerlan Idelbayev, Ahsan Mahmood, Aleksei Lebedev, Dishani Lahiri, Anujraaj Goyal, Ju Hu, Mingming Gong, Sergey Tulyakov, Anil Kag
2025 A* conf
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training.
CVPR
Jierun Chen, Dongting Hu, Xijie Huang, Huseyin Coskun, Arpit Sahni, Aarush Gupta, Anujraaj Goyal, Dishani Lahiri, Rajesh Singh, Yerlan Idelbayev, Junli Cao, Yanyu Li, Kwang-Ting Cheng, S.-H. Gary Chan, Mingming Gong, Sergey Tulyakov, Anil Kag, Yanwu Xu, Jian Ren
2024 A* conf
BitsFusion: 1.99 bits Weight Quantization of Diffusion Model.
NeurIPS
Yang Sui, Yanyu Li, Anil Kag, Yerlan Idelbayev, Junli Cao, Ju Hu, Dhritiman Sagar, Bo Yuan, Sergey Tulyakov, Jian Ren
2024 J jnl
BitsFusion: 1.99 bits Weight Quantization of Diffusion Model.
CoRR
Yang Sui, Yanyu Li, Anil Kag, Yerlan Idelbayev, Junli Cao, Ju Hu, Dhritiman Sagar, Bo Yuan, Sergey Tulyakov, Jian Ren
2024 J jnl
E
CoRR
Yifan Gong, Zheng Zhan, Qing Jin, Yanyu Li, Yerlan Idelbayev, Xian Liu, Andrey Zharkov, Kfir Aberman, Sergey Tulyakov, Yanzhi Wang, Jian Ren
2024 A* conf
E2GAN: Efficient Training of Efficient GANs for Image-to-Image Translation.
ICML
Yifan Gong, Zheng Zhan, Qing Jin, Yanyu Li, Yerlan Idelbayev, Xian Liu, Andrey Zharkov, Kfir Aberman, Sergey Tulyakov, Yanzhi Wang, Jian Ren
2024 — conf
Efficient Training with Denoised Neural Weights.
ECCV (83)
Yifan Gong, Zheng Zhan, Yanyu Li, Yerlan Idelbayev, Andrey Zharkov, Kfir Aberman, Sergey Tulyakov, Yanzhi Wang, Jian Ren
2024 J jnl
Efficient Training with Denoised Neural Weights.
CoRR
Yifan Gong, Zheng Zhan, Yanyu Li, Yerlan Idelbayev, Andrey Zharkov, Kfir Aberman, Sergey Tulyakov, Yanzhi Wang, Jian Ren
2024 J jnl
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training.
CoRR
Dongting Hu, Jierun Chen, Xijie Huang, Huseyin Coskun, Arpit Sahni, Aarush Gupta, Anujraaj Goyal, Dishani Lahiri, Rajesh Singh, Yerlan Idelbayev, Junli Cao, Yanyu Li, Kwang-Ting Cheng, S.-H. Gary Chan, Mingming Gong, Sergey Tulyakov, Anil Kag, Yanwu Xu, Jian Ren
2024 J jnl
TextCraftor: Your Text Encoder Can be Image Quality Controller.
CoRR
Yanyu Li, Xian Liu, Anil Kag, Ju Hu, Yerlan Idelbayev, Dhritiman Sagar, Yanzhi Wang, Sergey Tulyakov, Jian Ren
2024 A* conf
TextCraftor: Your Text Encoder can be Image Quality Controller.
CVPR
Yanyu Li, Xian Liu, Anil Kag, Ju Hu, Yerlan Idelbayev, Dhritiman Sagar, Yanzhi Wang, Sergey Tulyakov, Jian Ren
2022 Misc conf
Exploring the Effect of ℓ0/ℓ2 Regularization in Neural Network Pruning using the LC Toolkit.
ICASSP
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2021 B conf
An Empirical Comparison of Quantization, Pruning and Low-rank Neural Network Compression using the LC Toolkit.
IJCNN
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2021 B conf
Beyond Flops In Low-Rank Compression Of Neural Networks: Optimizing Device-Specific Inference Runtime.
ICIP
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2021 A conf
LC: A Flexible, Extensible Open-Source Toolkit for Model Compression.
CIKM
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2021 — —
Low-rank Compression of Neural Networks: LC Algorithms and Open-source Implementation.
Yerlan Idelbayev
2021 J jnl
Model compression as constrained optimization, with application to neural nets. Part V: combining compressions.
CoRR
Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev
2021 — conf
More General and Effective Model Compression via an Additive Combination of Compressions.
ECML/PKDD (3)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2021 B conf
Neural Network Compression via Additive Combination of Reshaped, Low-Rank Matrices.
DCC
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2021 A* conf
Optimal Quantization Using Scaled Codebook.
CVPR
Yerlan Idelbayev, Pavlo Molchanov, Maying Shen, Hongxu Yin, Miguel Á. Carreira-Perpiñán, José M. Álvarez
2021 Misc conf
Optimal Selection of Matrix Shape and Decomposition Scheme for Neural Network Compression.
ICASSP
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2020 J jnl
A flexible, extensible software framework for model compression based on the LC algorithm.
CoRR
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2020 A* conf
Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer.
CVPR
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2020 A* conf
Structured Multi-Hashing for Model Compression.
CVPR
Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2019 J jnl
Structured Multi-Hashing for Model Compression.
CoRR
Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2018 A* conf
"Learning-Compression" Algorithms for Neural Net Pruning.
CVPR
Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev
2017 J jnl
Model compression as constrained optimization, with application to neural nets. Part II: quantization.
CoRR
Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev