Zhang, Ce

Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features

Yu, K.-H., Zhang, C., Berry, G. J., Altman, R. B., Ré, C., Rubin, D. L., & Snyder, M. (2016) · Nature Communications

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting

Cao, D., Wang, Y., Duan, J., Zhang, C., Zhu, X., Huang, C., Tong, Y., Xu, B., Bai, J., Tong, J., et al. (2021) · arXiv

Time Series Analysis and ForecastingTraffic Prediction and Management Techniques

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Mixture-of-Agents Enhances Large Language Model Capabilities

Wang, J., Wang, J., Athiwaratkun, B., Zhang, C., & Zou, J. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

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Holistic Evaluation of Language Models

Liang, P., Bommasani, R., Lee, T., Tsipras, D., Soylu, D., Yasunaga, M., Zhang, Y., Narayanan, D., Wu, Y., Kumar, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 255

Generative adversarial networks recover features in astrophysical images of galaxies beyond the deconvolution limit

Schawinski, K., Zhang, C., Zhang, H., Fowler, L., & Santhanam, G. K. (2017) · Monthly Notices of the Royal Astronomical Society: Letters

Advanced Image Processing TechniquesImage and Signal Denoising Methods

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Communication Compression for Decentralized Training

Tang, H., Gan, S., Zhang, C., Zhang, T., & Liu, J. (2018) · arXiv

Stochastic Gradient Optimization TechniquesDistributed Control Multi-Agent Systems

Cited by 206

Using transfer learning to detect galaxy mergers

Ackermann, S., Schawinski, K., Zhang, C., Weigel, A. K., & Turp, M. D. (2018) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAdvanced Neural Network Applications

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FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU

Sheng, Y., Zheng, L., Yuan, B., Li, Z., Ryabinin, M., Fu, D. Y., Xie, Z., Chen, B., Barrett, C., Gonzalez, J. E., et al. (2023) · arXiv

Parallel Computing and Optimization TechniquesNatural Language Processing Techniques

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FPGA-Accelerated Dense Linear Machine Learning: A Precision-Convergence Trade-Off

Kara, K., Alistarh, D., Alonso, G., Mutlu, O., & Zhang, C. (2017) · 2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)

Embedded Systems Design TechniquesNumerical Methods and Algorithms

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Distributed learning over unreliable networks

Yu, C., Tang, H., Renggli, C., Kassing, S., Singla, A., Alistarh, D., Zhang, C., & Liu, J. (2018) · arXiv

Stochastic Gradient Optimization TechniquesDistributed systems and fault tolerance

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Building Continuous Integration Services for Machine Learning

Karlaš, B., Interlandi, M., Renggli, C., Wu, W., Zhang, C., Mukunthu Iyappan Babu, D., Edwards, J., Lauren, C., Xu, A., & Weimer, M. (2020) · Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Software Engineering Techniques and PracticesSoftware Engineering Research

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psfgan: a generative adversarial network system for separating quasar point sources and host galaxy light

Stark, D., Launet, B., Schawinski, K., Zhang, C., Koss, M., Turp, M. D., Sartori, L. F., Zhang, H., Chen, Y., & Weigel, A. K. (2018) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

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FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data

Xie, Y., Wang, Z., Li, Y., Ding, B., Gürel, N. M., Zhang, C., Huang, M., Lin, W., & Zhou, J. (2021) · Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining

Recommender Systems and TechniquesAdvanced Graph Neural Networks

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DataPerf: Benchmarks for Data-Centric AI Development

Mazumder, M., Banbury, C., Yao, X., Karlaš, B., Rojas, W. G., Diamos, S., Diamos, G., He, L., Parrish, A., Kirk, H. R., et al. (2023) · Advances in Neural Information Processing Systems 36

Advanced Database Systems and QueriesScientific Computing and Data Management

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Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions

Massaroli, S., Poli, M., Fu, D., Kumbong, H., Parnichkun, R., Romero, D., Timalsina, A., McIntyre, Q., Chen, B., Rudra, A., et al. (2023) · Advances in Neural Information Processing Systems 36

Mathematical Analysis and Transform MethodsNeural Networks and Applications

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Mechanistic Design and Scaling of Hybrid Architectures

Poli, M., Thomas, A. W., Nguyen, E., Ponnusamy, P., Deiseroth, B., Kersting, K., Suzuki, T., Hie, B., Ermon, S., Ré, C., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

Squeeze Evolve: Unified Multi-Model Orchestration for Verifier-Free Evolution

Maheswaran, M., Lakhani, L., Zhou, Z., Yang, S., Wang, J., Hooper, C., Hu, Y., Tiwari, R., Wang, J., Singh, H., et al. (2026) · arXiv

Evolutionary Algorithms and ApplicationsSoftware Engineering Research

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