Towards Training Reproducible Deep Learning Models

Towards Training Reproducible Deep Learning Models

4 February 2022

Gopi Krishnan Rajbahadur

Papers citing "Towards Training Reproducible Deep Learning Models"

16 / 16 papers shown

Title
Software Performance Engineering for Foundation Model-Powered Software (FMware) Haoxiang Zhang Shi Chang Arthur Leung Kishanthan Thangarajah Boyuan Chen Hanan Lutfiyya Ahmed E. Hassan 66 1 0 14 Nov 2024
Watson: A Cognitive Observability Framework for the Reasoning of LLM-Powered Agents Benjamin Rombaut Sogol Masoumzadeh Kirill Vasilevski Dayi Lin Ahmed E. Hassan LRM 26 0 0 05 Nov 2024
Investigating the Impact of Randomness on Reproducibility in Computer Vision: A Study on Applications in Civil Engineering and Medicine Bahadır Eryılmaz Osman Alperen Koras Jorg Schlotterer Christin Seifert 11 0 0 19 Sep 2024
Studying the Impact of TensorFlow and PyTorch Bindings on Machine Learning Software Quality Hao Li Gopi Krishnan Rajbahadur C. Bezemer 19 5 0 07 Jul 2024
Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers Harald Semmelrock Tony Ross-Hellauer Simone Kopeinik Dieter Theiler Armin Haberl Stefan Thalmann Dominik Kowald 65 6 0 20 Jun 2024
Artifact Evaluation for Distributed Systems: Current Practices and Beyond Mohammad Reza Saleh Sedghpour Alessandro Vittorio Papadopoulos Cristian Klein Johan Tordsson 13 0 0 18 Jun 2024
Beyond the Black Box: Do More Complex Models Provide Superior XAI Explanations? Mateusz Cedro Marcin Chlebus 25 1 0 14 May 2024
Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research Tobias Hille Maximilian Stubbemann Tom Hanika AI4CE 30 0 0 13 Mar 2024
Investigating Reproducibility in Deep Learning-Based Software Fault Prediction Adil Mukhtar Dietmar Jannach Franz Wotawa AI4CE 22 0 0 08 Feb 2024
Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study Mehil B. Shah Mohammad Masudur Rahman Foutse Khomh 20 4 0 05 Jan 2024
Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey Xinyu She Yue Liu Yanjie Zhao Yiling He Li Li C. Tantithamthavorn Zhan Qin Haoyu Wang ELM 30 13 0 27 Oct 2023
Variance of ML-based software fault predictors: are we really improving fault prediction? Xhulja Shahini Domenic Bubel Andreas Metzger AAML 11 1 0 26 Oct 2023
Attention is Not Always What You Need: Towards Efficient Classification of Domain-Specific Text Yasmen Wahba N. Madhavji John Steinbacher 25 0 0 31 Mar 2023
Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision Wenxin Jiang Vishnu Banna Naveen Vivek Abhinav Goel Nicholas Synovic George K. Thiruvathukal James C. Davis VLM 26 18 0 13 Mar 2023
Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues Riccardo Albertoni Sara Colantonio Piotr Skrzypczyñski J. Stefanowski 13 10 0 24 Feb 2023
Estimation of Over-parameterized Models from an Auto-Modeling Perspective Yiran Jiang Chuanhai Liu 14 1 0 03 Jun 2022