Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification von Zhang, Quanshi, Cheng, Xu, Chen, Yilan, Rao, Zhefan

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High‐Performance, Micrometer Thick/Conformal, Transparent Metal‐Network Electrodes for Flexible and Curved Electronic Devices von Liu, Jianpeng, Xiao, Lin, Rao, Zhefan, Dong, Biyang, Yin, Zhouping, Huang, YongAn

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ENTED: Enhanced Neural Texture Extraction and Distribution for Reference-based Blind Face Restoration von Lau, Yuen-Fui, Zhang, Tianjia, Rao, Zhefan, Chen, Qifeng

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LDM-ISP: Enhancing Neural ISP for Low Light with Latent Diffusion Models von Wen, Qiang, Xing, Yazhou, Rao, Zhefan, Chen, Qifeng

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Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification von Zhang, Quanshi, Cheng, Xu, Chen, Yilan, Rao, Zhefan

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement von Rao, Zhefan, Ji, Liya, Xing, Yazhou, Liu, Runtao, Liu, Zhaoyang, Xie, Jiaxin, Peng, Ziqiao, He, Yingqing, Chen, Qifeng

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LDM-ISP: Enhancing Neural ISP for Low Light with Latent Diffusion Models von Wen, Qiang, Xing, Yazhou, Rao, Zhefan, Chen, Qifeng

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Explaining Knowledge Distillation by Quantifying the Knowledge von Cheng, Xu, Rao, Zhefan, Chen, Yilan, Zhang, Quanshi

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Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification von Zhang, Quanshi, Xu, Cheng, Chen, Yilan, Rao, Zhefan

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Explaining Knowledge Distillation by Quantifying the Knowledge von Xu, Cheng, Rao, Zhefan, Chen, Yilan, Zhang, Quanshi

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Decoding children's social behavior von Rehg, J. M., Abowd, G. D., Rozga, A., Romero, Mario, Clements, M. A., Sclaroff, S., Essa, I., Ousley, O. Y., Li, Y., Kim, C., Rao, H., Kim, J. C., Presti, L. L., Zhang, J., Lantsman, D., Bidwell, J., Ye, Z.

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