Last update: 2023/12/26


A preprint is a scientific manuscript that authors post on an open platform (usually before or in parallel with the journal's peer review process). GitData Archive is an open access online archive and service for preprints.

The purpose of GitData Archive is to increase the openness and accessibility of scientific results, increase collaboration among researchers, document the origins of ideas, and inform ongoing and planned research through more timely reporting of completed studies.

By posting preprints on GitData Archive, authors have the opportunity to instantly familiarize the scientific community with the results of their research and receive feedback from colleagues before publication in the journal.

Content on GitData Archive is pre-moderated, but not reviewed. You can search through uploaded preprints or view the latest uploaded preprints in your area of interest.

Available Subjects

Data Science / Statistics

  1. Applications: Covers statistical applications in Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, and Social Sciences.
  2. Computation: Focuses on statistical algorithms, simulation, and visualization.
  3. Machine Learning: Encompasses machine learning papers with a statistical or theoretical grounding, including supervised, unsupervised, and reinforcement learning.
  4. Methodology: Encompasses statistical methodologies in Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, and Nonparametric Methods.
  5. Other Statistics: Encompasses work in statistics that does not fit into other statistical classifications.
  6. Statistics Theory: Covers statistical theory topics including Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, and Testing.

Electrical Engineering / Computer Science

  1. Artificial Intelligence: Focuses on Expert Systems, Theorem Proving, Knowledge Representation, Planning, and Uncertainty in AI.
  2. Audio and Speech Processing: Focuses on processing signals for audio, speech, and language.
  3. Computation and Language: Encompasses Natural Language Processing, Computational Linguistics, Speech, and Text Retrieval.
  4. Computational Complexity: Deals with Models of Computation, Complexity Classes, Structural Complexity, and Complexity Tradeoffs.
  5. Computational Engineering, Finance, and Science: Explores applications of computer science in modeling complex systems in science, engineering, and finance, often requiring supercomputing or distributed computing.
  6. Computational Geometry: Involves Geometric Algorithms and Computational Geometry.
  7. Computer Science and Game Theory: Covers theoretical and applied aspects at the intersection of computer science and game theory, including mechanism design, learning in games, and agent modeling.
  8. Computer Vision and Pattern Recognition: Encompasses Image Processing, Pattern Recognition, and Scene Understanding.
  9. Computers and Society: Explores the impact of computers on society, including computer ethics, legal aspects, and computers in education.
  10. Cryptography and Security: Encompasses all areas of cryptography and security, including authentication, public key cryptosystems, and proof-carrying code.
  11. Data Structures and Algorithms: Covers data structures and the analysis of algorithms.
  12. Image and Video Processing: Involves theory, algorithms, and architectures for handling images and video signals.
  13. Signal Processing: Encompasses theory, algorithms, and applications for signal and data analysis.
  14. Systems and Control: Covers research on automatic control systems and applications in various fields.