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Kyle Ira Harrington
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2020 – today
- 2023
- [j11]Kai Fan
, Ranil Dhammapala, Kyle Ira Harrington
Machine learning-based ozone and PM2.5 forecasting: Application to multiple AQS sites in the Pacific Northwest. Frontiers Big Data 6 (2023) - 2022
- [j10]Kai Fan
Development of a Machine Learning Approach for Local-Scale Ozone Forecasting: Application to Kennewick, WA. Frontiers Big Data 5: 781309 (2022) - 2021
- [j9]Leo Epstein, Zeth Dubois
Complex population dynamics in a spatial microbial ecosystem with Physarum polycephalum. Biosyst. 208: 104483 (2021) - 2020
- [c19]Ulrik Günther
Bionic Tracking: Using Eye Tracking to Track Biological Cells in Virtual Reality. ECCV Workshops (1) 2020: 280-297 - [c18]Ulrik Günther
Tales from the Trenches: Developing sciview, a new 3D viewer for the ImageJ community. VisGap@Eurographics/EuroVis 2020: 69-75 - [i5]Ulrik Günther
Tales from the Trenches: Developing sciview, a new 3D viewer for the ImageJ community. CoRR abs/2004.11897 (2020) - [i4]Ulrik Günther
Bionic Tracking: Using Eye Tracking to Track Biological Cells in Virtual Reality. CoRR abs/2005.00387 (2020)
2010 – 2019
- 2019
- [j8]Kyle Ira Harrington, Jordan B. Pollack:
Escalation of Memory Length in Finite Populations. Artif. Life 25(1): 22-32 (2019) - [c17]Ulrik Günther
scenery: Flexible Virtual Reality Visualization on the Java VM. IEEE VIS (Short Papers) 2019: 166-170 - [i3]Ulrik Günther
scenery - Flexible Virtual Reality Visualisation on the Java VM. CoRR abs/1906.06726 (2019) - 2018
- [j7]Sylvain Cussat-Blanc, Kyle Ira Harrington, Wolfgang Banzhaf:
Artificial Gene Regulatory Networks - A Review. Artif. Life 24(4) (2018) - [j6]Kyle I. S. Harrington
FunImageJ: a Lisp framework for scientific image processing. Bioinform. 34(5): 899-900 (2018) - [j5]Susan J. Crawford-Young, Smat Dittapongpitch, Richard Gordon, Kyle I. S. Harrington
Acquisition and reconstruction of 4D surfaces of axolotl embryos with the flipping stage robotic microscope. Biosyst. 173: 214-220 (2018) - [i2]Dennis G. Wilson, Kyle Ira Harrington, Sylvain Cussat-Blanc, Hervé Luga:
Evolving Differentiable Gene Regulatory Networks. CoRR abs/1807.05948 (2018) - [i1]Dennis G. Wilson, Sylvain Cussat-Blanc, Hervé Luga, Kyle Ira Harrington:
Neuromodulated Learning in Deep Neural Networks. CoRR abs/1812.03365 (2018) - 2016
- [j4]Kyle I. S. Harrington:
Wolfgang Banzhaf and Lidia Yamamoto: Artificial Chemistries, MIT Press, 2015. Genet. Program. Evolvable Mach. 17(3): 317-319 (2016) - [j3]Kyle I. S. Harrington:
A circuit basis for morphogenesis. Theor. Comput. Sci. 633: 28-36 (2016) - 2015
- [j2]Sylvain Cussat-Blanc, Kyle Ira Harrington, Jordan B. Pollack
Gene Regulatory Network Evolution Through Augmenting Topologies. IEEE Trans. Evol. Comput. 19(6): 823-837 (2015) - [c16]Sylvain Cussat-Blanc, Kyle Ira Harrington:
Genetically-regulated Neuromodulation Facilitates Multi-Task Reinforcement Learning. GECCO 2015: 551-558 - 2014
- [c15]Jessica Lowell, Kyle Ira Harrington, Jordan B. Pollack:
The Resistance of Swarm Ecosystem Under Environmental Variation. ALIFE 2014: 827-834 - 2013
- [c14]Kyle Ira Harrington, Emmanuel Awa, Sylvain Cussat-Blanc, Jordan B. Pollack:
Robot coverage control by evolved neuromodulation. IJCNN 2013: 1-8 - 2012
- [c13]Kyle Ira Harrington, A. Pinar Ozisik, Jordan B. Pollack:
The Effects of Finite Populations and Selection on the Emergence of Signaling. ALIFE 2012 - [c12]Kyle Ira Harrington, Lee Spector, Jordan B. Pollack, Una-May O'Reilly:
Autoconstructive evolution for structural problems. GECCO (Companion) 2012: 75-82 - [c11]A. Pinar Ozisik, Kyle Ira Harrington:
The effects of tags on the evolution of honest signaling. GECCO (Companion) 2012: 345-352 - [c10]Lee Spector, Kyle Ira Harrington, Thomas Helmuth:
Tag-based modularity in tree-based genetic programming. GECCO 2012: 815-822 - 2011
- [c9]Lee Spector, Thomas Helmuth, Kyle Ira Harrington:
Fecundity and selectivity in evolutionary computation. GECCO (Companion) 2011: 129-130 - [c8]Lee Spector, Brian Martin, Kyle Ira Harrington, Thomas Helmuth:
Tag-based modules in genetic programming. GECCO 2011: 1419-1426 - [c7]Kyle Ira Harrington, Megan M. Olsen, Hava T. Siegelmann:
Communicated somatic markers benefit both the individual and the species. IJCNN 2011: 3272-3278 - 2010
- [j1]Megan M. Olsen, Kyle Ira Harrington, Hava T. Siegelmann:
Conspecific Emotional Cooperation Biases Population Dynamics: A Cellular Automata Approach. Int. J. Nat. Comput. Res. 1(3): 51-65 (2010) - [c6]Michael Heymann, Kyle Ira Harrington, Jordan B. Pollack, Seth Fraden:
En Route to Signal Inversion in Chemical Computing. ALIFE 2010: 166-167 - [c5]Kyle Ira Harrington, Jordan B. Pollack
Robot phylogenetics. GECCO (Companion) 2010: 2077-2078
2000 – 2009
- 2008
- [c4]Megan M. Olsen, Kyle Ira Harrington, Hava T. Siegelmann:
Emotions for Strategic Real-Time Systems. AAAI Spring Symposium: Emotion, Personality, and Social Behavior 2008: 104-110 - 2007
- [c3]Kyle Ira Harrington:
Predicting reactions from amino acid sequences in S. cerevisiae: an evolutionary computation approach. GECCO (Companion) 2007: 2725-2728 - 2006
- [c2]Kyle Ira Harrington, Hava T. Siegelmann:
Adaptive Multi-modal Sensors. 50 Years of Artificial Intelligence 2006: 164-173 - 2005
- [c1]Lee Spector, Jon Klein, Kyle Ira Harrington, Raymond Coppinger:
Teaching the evolution of behavior with SuperDuperWalker. AIED 2005: 923-925
Coauthor Index
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