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I-shapedSpecialist — deep expertise in Python
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This is the implement repository of our upcoming ESEC/FSE 2020 paper: Deep Learning Library Testing via Effective Model Generation.
This is the implementation repository of our incoming ESEC/FSE 2021 paper: Exposing Numerical Bugs in Deep Learning via GradientBack-propagation.
This is the homepage of our JSEP paper: Revisiting Deep Neural Network Test Coverage from the Test Effectiveness Perspective
This is the webpage of our ICSE 2023 SEIP paper: Achieving Last-Mile Functional Coverage in Testing Chip Design Software Implementations
This repository contains the issues and posts of our work An Empirical Study on Numerical Bugs in Deep Learning Programs. We list these issues and posts in four markdown files as follows.
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Skill package for ML/CV/NLP paper writing, curated and adapted from Prof. Peng Sida's open notes for Codex, Claude Code, and Gemini.
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