Publications


Filters:


Results for: others

Precision Psychiatry with Immunological and Cognitive Biomarkers: A Multi-Domain Prediction for the Diagnosis of Bipolar Disorder or Schizophrenia Using Machine Learning

B. S. Fernandes, C. Karmakar, R. Tamouza, T. Tran, J. Yearwood, N. Hamdani, H. Laouamri, J. Richard, R. Yolken, M. Berk, O.

2020 / Vol. 10, pp. 1 - 13 / Translational psychiatry

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization

S. Gupta, S. Rana, S. Venkatesh, O.

2020 / Vol. 34, pp. 2425 - 2432 / Proceedings of the AAAI Conference on Artificial Intelligence

Accelerated Bayesian Optimisation through Weight-Prior Tuning

A. Shilton, S. Gupta, S. Rana, P. Vellanki, C. Li, S. Venkatesh, L. Park, A. Sutti, D. Rubin, T. Dorin, O.

2020 / pp. 635 - 645 / Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)

Improving the Tensile Properties of Wet Spun Silk Fibers Using Rapid Bayesian Algorithm

Y. Yao, B. Allardyce, R. Rajkhowa, D. Hegh, A. Sutti, S. Subianto, S. Gupta, S. Rana, S. Greenhill, S. Venkatesh, O.

2020 / Vol. 6, pp. 3197 - 3207 / ACS Biomaterials Science & Engineering

Efficient Bayesian Function Optimization of Evolving Material Manufacturing Processes

D. Rubín, D. Nguyen, P. Vellanki, C. Li, S. Rana, N. Thompson, S. Gupta, K. Pringle, S. Subianto, S. Venkatesh, O.

2019 / Vol. 4, pp. 20571 - 20578 / ACS omega

Bayesian Optimization with Unknown Search Space

H. Ha, S. Rana, S. Gupta, T. Nguyen, S. Venkatesh, O.

2019 / pp. 11772 - 11781 / Advances in Neural Information Processing Systems

Accelerating Experimental Design by Incorporating Experimenter Hunches.

C. Li, S. Rana, S. Gupta, V. Nguyen, S. Venkatesh, A. Sutti, C. de, T. Slezak, M. Height, M. Mohammed, O.

2018 / pp. 257 - 266 / 2018 IEEE International Conference on Data Mining (ICDM)

Accelerating Experimental Design by Incorporating Experimenter Hunches

C. Li, S. Rana, S. Gupta, V. Nguyen, S. Venkatesh, A. Sutti, C. de, T. Slezak, M. Height, M. Mohammed, O.

2018 / pp. 257 - 266 / 2018 IEEE International Conference on Data Mining (ICDM)

Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view

W. Luo, D. Phung, T. Tran, S. Gupta, S. Rana, C. Karmakar, A. Shilton, J. Yearwood, N. Dimitrova, T. Ho, O.

2016 / Vol. 18, pp. e323 / Journal of medical Internet research

Randomised controlled trial of an iPad based early intervention for autism: TOBY playpad study protocol

J. Granich, A. Dass, M. Busacca, D. Moore, A. Anderson, S. Venkatesh, T. Duong, P. Vellanki, A. Richdale, D. Trembath, O.

2016 / Vol. 16, pp. 167 / BMC pediatrics

An Analysis of the Mobile App Review Landscape: Trends and Implications

L. Hoon, R. Vasa, J. Schneider, J. Grundy, O.

2013 / Faculty of Information and Communication Technologies, Swinburne University of Technology, Tech. Rep

Towards Discovery of Influence and Personality Traits through Social Link Prediction.

T. Nguyen, D. Phung, B. Adams, S. Venkatesh, O.

2011 / pp. 566 - 569 / ICWSM: 5th AAAI International Conference on Weblogs and Social Media

Probabilistic Models over Ordered Partitions with Applications in Document Ranking and Collaborative Filtering

T. Tran, D. Phung, S. Venkatesh, O.

2011 / pp. 426 - 437 / Proceedings of the 2011 SIAM International Conference on Data Mining (SDM)

Data Files Used to Study Change Dynamics in Software Systems

R. Vasa, O.

2010

Data Files Used to Study the Distribution of Growth in Software Systems

R. Vasa, O.

2010

Raw Metrics for Measuring Software Evolution in Open Source Software Systems

R. Vasa, O.

2010