8 citations · 20 across the 19 of their papers we have counts for
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q-bio.QM2023★ 8 cited
ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing
Zhi Jin, Sheng Xu, Xiang Zhang +6
De novo peptide sequencing from mass spectrometry (MS) data is a critical task in proteomics research. Traditional de novo algorithms have encountered a bottleneck in accuracy due…
cs.AI2023★ 3 cited
Toward Understanding BERT-Like Pre-Training for DNA Foundation Models
Chaoqi Liang, Lifeng Qiao, Peng Ye +9
With the success of large-scale pre-training in language tasks, there is an increasing trend of applying it to the domain of life sciences. In particular, pre-training methods base…
cs.AI2023
zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning
Zhipeng Wang, Nanqing Dong, Jiahao Sun +2
Federated learning (FL) is a machine learning paradigm, which enables multiple and decentralized clients to collaboratively train a model under the orchestration of a central aggre…