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Cornell University
- [email protected]
- https://scholar.google.com/citations?hl=en&user=OgIdbfAAAAAJ
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BiB_ADV-SCI--DL_for_Peptide Public
We provide a peptide self-assembly dataset in this project. On this dataset, we provide graph- and sequence-based deep learning methods for peptides as a tool library.
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CIKM22--AtkSE Public
The pytorch implementation for paper 'Are Gradients on Graph Structure Reliable in Gray-box Attacks?'
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Florence2-SAM2 Public
A prompt-free video segmentation tool based on Florence 2 and SAM 2.
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GroundingDINO-SAM2 Public
A text prompt video segmentation tool based on GroundingDINO and SAM2
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JMI--RepCon Public
Implementation for paper Co-modeling the Sequential and Graphical Routes for Peptide Representation Learning
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NeurIPS22--GraD Public
PyTorch Implementation for NeurIPS 2022 paper 'Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias'
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SpatialLM Public
Forked from manycore-research/SpatialLMSpatialLM: Large Language Model for Spatial Understanding
Python Other UpdatedMar 17, 2025