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2020 – today
- 2025
[i3]Aishwarya Kamath, Johan Ferret, Shreya Pathak, Nino Vieillard, Ramona Merhej, Sarah Perrin, Tatiana Matejovicova, Alexandre Ramé, Morgane Rivière, Louis Rouillard, Thomas Mesnard, Geoffrey Cideron, Jean-Bastien Grill, Sabela Ramos, Edouard Yvinec, Michelle Casbon, Etienne Pot, Ivo Penchev, Gaël Liu, Francesco Visin, Kathleen Kenealy, Lucas Beyer, Xiaohai Zhai, Anton Tsitsulin, Róbert Busa-Fekete, Alex Feng, Noveen Sachdeva, Benjamin Coleman, Yi Gao, Basil Mustafa, Iain Barr, Emilio Parisotto, David Tian, Matan Eyal, Colin Cherry, Jan-Thorsten Peter, Danila Sinopalnikov, Surya Bhupatiraju, Rishabh Agarwal, Mehran Kazemi, Dan Malkin, Ravin Kumar, David Vilar, Idan Brusilovsky, Jiaming Luo, Andreas Steiner, Abe Friesen, Abhanshu Sharma, Abheesht Sharma, Adi Mayrav Gilady, Adrian Goedeckemeyer, Alaa Saade, Alexander Kolesnikov, Alexei Bendebury, Alvin Abdagic, Amit Vadi, András György, André Susano Pinto, Anil Das, Ankur Bapna, Antoine Miech, Antoine Yang, Antonia Paterson, Ashish Shenoy, Ayan Chakrabarti, Bilal Piot, Bo Wu, Bobak Shahriari, Bryce Petrini, Charlie Chen, Charline Le Lan, Christopher A. Choquette-Choo, CJ Carey, Cormac Brick, Daniel Deutsch, Danielle Eisenbud, Dee Cattle, Derek Cheng, Dimitris Paparas, Divyashree Shivakumar Sreepathihalli, Doug Reid, Dustin Tran, Dustin Zelle, Eric Noland, Erwin Huizenga, Eugene Kharitonov, Frederick Liu, Gagik Amirkhanyan, Glenn Cameron, Hadi Hashemi, Hanna Klimczak-Plucinska, Harman Singh, Harsh Mehta, Harshal Tushar Lehri, Hussein Hazimeh, Ian Ballantyne, Idan Szpektor, Ivan Nardini:
Gemma 3 Technical Report. CoRR abs/2503.19786 (2025)- 2024
- [c12]David Tian, Hazel Y. Squires, Charlotte Buckley, Duncan Gillespie
, Harry Tattan-Birch, Lion Shahab, Robert West, Alan Brennan, Jamie Brown, Robin C. Purshouse:
Incorporating the COM-B Model for Behavior Change into an Agent-Based Model of Smoking Behaviors: An Object-Oriented Design. WSC 2024: 252-263 - 2023
- [j4]David Tian, Zi-Qiang Lang, Di Zhang, Dilly O. Anumba:
A filter-predictor polynomial feature based machine learning approach to predicting preterm birth from cervical electrical impedance spectroscopy. Biomed. Signal Process. Control. 80(Part): 104345 (2023) - [c11]Esha Uboweja, David Tian, Qifei Wang, Yi-Chun Kuo, Joe Zou, Lu Wang, George Sung, Matthias Grundmann:
On-device Real-time Custom Hand Gesture Recognition. ICCV (Workshops) 2023: 4275-4279 - [i2]Esha Uboweja, David Tian, Qifei Wang, Yi-Chun Kuo, Joe Zou, Lu Wang, George Sung, Matthias Grundmann:
On-device Real-time Custom Hand Gesture Recognition. CoRR abs/2309.10858 (2023) - 2022
- [i1]Jamie Menjay Lin, Siargey Pisarchyk, Juhyun Lee, David Tian, Tingbo Hou, Karthik Raveendran, Raman Sarokin, George Sung, Trent Tolley, Matthias Grundmann:
Efficient Heterogeneous Video Segmentation at the Edge. CoRR abs/2208.11666 (2022) - 2021
- [c10]Gordon Hendry, Seth Harris, Ryan Goodwin, Leonid Neverov, Yunkai Xiao, David Tian, Yang Song:
PyRoboCar: A Low-cost Deep Neural Network-based Autonomous Car. FIE 2021: 1-5
2010 – 2019
- 2018
- [j3]David Tian, Jiamei Deng, Gopika Vinod, T. V. Santhosh, Hissam Tawfik:
A constraint-based genetic algorithm for optimizing neural network architectures for detection of loss of coolant accidents of nuclear power plants. Neurocomputing 322: 102-119 (2018) - [c9]David Tian, Jiamei Deng, Gopika Vinod, T. V. Santhosh:
A Constraint-Based Random Search Algorithm for Optimizing Neural Network Architectures and Ensemble Construction in Detecting Loss of Coolant Accidents in Nuclear Power Plants. DeSE 2018: 237-243 - [c8]David Tian, Jiamei Deng, Enrico Zio, Francesco Di Maio, Fucheng Liao:
Failure Modes Detection of Nuclear Systems Using Machine Learning. DSA 2018: 35-43 - [p1]David Tian, Jiamei Deng, Gopika Vinod, T. V. Santhosh, Hissam Tawfik:
A Neural Networks Design Methodology for Detecting Loss of Coolant Accidents in Nuclear Power Plants. Applications of Big Data Analytics 2018: 43-61 - 2013
- [c7]Laurie Hirsch, David Tian:
Txt2vz: A New Tool for Generating Graph Clouds. ICCS 2013: 322-331 - [c6]Ratnesh Sahay, Dimitrios Ntalaperas, Eleni Kamateri, Panagiotis Hasapis, Oya Deniz Beyan, Marie-Pierre F. Strippoli, Christiana Demetriou, Thomai Gklarou-Stavropoulou, Mathias Brochhausen, Konstantinos A. Tarabanis, Thanassis Bouras, David Tian, Aristos Aristodimou, Athos Antoniades, Christos Georgousopoulos, Manfred Hauswirth, Stefan Decker:
An Ontology for Clinical Trial Data Integration. SMC 2013: 3244-3250 - [c5]David Tian, Ann Gledson, Athos Antoniades, Aristos Aristodimou, Dimitrios Ntalaperas, Ratnesh Sahay, Jianxin Pan, Stavros Stivaros, Goran Nenadic, Xiao-Jun Zeng, John A. Keane:
A Bayesian Association Rule Mining Algorithm. SMC 2013: 3258-3264 - 2012
- [c4]David Tian, L. Richard Carley, David S. Ricketts:
Frequency scaling of power reclamation networks in outphasing PA architectures. ISCAS 2012: 1058-1061 - 2011
- [j2]David Tian, Xiao-Jun Zeng, John A. Keane:
Core-generating approximate minimum entropy discretization for rough set feature selection in pattern classification. Int. J. Approx. Reason. 52(6): 863-880 (2011) - [j1]David Tian, Xiao-Jun Zeng, John A. Keane:
Core-Generating Discretization for Rough Set Feature Selection. Trans. Rough Sets 13: 135-158 (2011) - 2010
- [c3]David Tian, Keith Burley:
Classification of micro-array gene expression data using neural networks. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [b1]David Tian:
Effective rough set feature selection via core-generating approximate minimum entropy discretization. University of Manchester, UK, 2009 - 2007
- [c2]David Tian, John A. Keane, Xiao-Jun Zeng:
Core-generating Approximate Minimum Entropy Discretization for Rough Set Feature Selection: An Experimental Investigation. FUZZ-IEEE 2007: 1-6 - 2006
- [c1]David Tian, John A. Keane, Xiao-Jun Zeng:
Evaluating the effect of rough set feature selection on the performance of decision trees. GrC 2006: 57-62
Coauthor Index
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