The articles and other works listed here provide background and deeper insight into some of the topics to be discussed at the IACS Brain + Machines Symposium. Items marked with a ✽ are by participants in the symposium or their research groups.
✽ Narayanan Kasthuri, Kenneth Jeffrey Hayworth, Daniel Raimund Berger, Richard Lee Schalek, José Angel Conchello, Seymour Knowles-Barley, Dongil Lee, Amelio Vázquez-Reina, Verena Kaynig, Thouis Raymond Jones, Mike Roberts, Josh Lyskowski Morgan, Juan Carlos Tapia, H. Sebastian Seung, William Gray Roncal, Joshua Tzvi Vogelstein, Randal Burns, Daniel Lewis Sussman, Carey Eldin Priebe, Hanspeter Pfister, and Jeff William Lichtman. 2015. Saturated reconstruction of a volume of neocortex. Cell 162:648–661. Abstract. Additional related resources.
✽ William R. Gray Roncal, Dean M. Kleissas, Joshua T. Vogelstein, Priya Manavalan, Kunal Lillaney, Michael Pekala, Randal Burns, R. Jacob Vogelstein, Carey E. Priebe, Mark A. Chevillet, and Gregory D. Hager. 2015. An automated images-to-graphs framework for high resolution connectomics. Frontiers in Neuroinformatics Vol. 9, Article 20. PDF.
✽ Xiaolong Jiang, Shan Shen, Cathryn R. Cadwell, Philipp Berens, Fabian Sinz, Alexander S. Ecker, Saumil Patel, and Andreas S. Tolias. 2015. Principles of connectivity among morphologically defined cell types in adult neocortex. Science 350:aac9462-1–10. Abstract.
✽ Jeff W. Lichtman and Winfried Denk. 2011. The big and the small: Challenges of imaging the brain's circuits. Science 334:618–623. Abstract.
✽ Nancy Kanwisher and Daniel D. Dilks. 2013. The functional organization of the ventral visual pathway in humans. In The New Visual Neurosciences, John S. Werner and Leo M. Chalupa, editors. Cambridge, MA: The MIT Press. PDF.
✽ Nancy Kanwisher. 2010. Functional specificity in the human brain: A window into the functional architecture of the mind. Proceedings of the National Academy of Sciences of the U.S.A. 107:11163–11170. PDF.
John C. Gore. 2003. Principles and practice of functional MRI of the human brain. Journal of Clinical Investigation 112(1):4–9. PDF.
✽ David Cox. 2014. Do we understand high-level vision? Current Opinion in Neurobiology 25:187–193. Abstract.
✽ Lotter, William, Gabriel Kreiman, and David Cox. 2015 preprint. Unsupervised learning of visual structure using predictive generative networks. arXiv.
Leslie G. Valiant. 2006. A quantitative theory of neural computation. Biological Cybernetics 95(3):205–211. Abstract.
Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Book in preparation. Deep Learning. Cambridge, MA: The MIT Press. Online preview edition.
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature 521:436–444. Abstract.
Brian Hayes. 2014. Delving into deep learning. American Scientist 102:186-189. PDF.
✽ Nicolas Maudet, Maria Silvia Pini, Francesca Rossi, and Kristen Brent Venable. 2012. Influence and aggregation of preferences over combinatorial domains. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012), Valencia, Spain. PDF.
Samuel J. Gershman, Eric J. Horvitz, and Joshua B. Tenenbaum. 2015. Computational rationality: A converging paradigm for intelligence in brains, minds, and machines. Science 349:273–278. Abstract.
Nils J. Nillson. 2010. The Quest for Artificial Intelligence: A History of Ideas and Achievements. Cambridge, UK: Cambridge University Press. PDF.
Li Deng and Dong Yu. 2013. Deep Learning Methods and Applications. Foundations and Trends in Signal Processing Volume 7 Issues 3-4. PDF.
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2012. ImageNet classification with deep convolutional neural networks. In Advances in Neural Information Processing Vol. 25. Cambridge, Mass: MIT Press. PDF.
Intelligence Advanced Research Projects Activity. 2016. Request for information: neurally inspired computing principles. Online document.
✽ Beipeng Mu, Ali-akbar Agha-mohammadi, Liam Paull, Matthew Graham, Jonathan How, and John Leonard. 2015. Two-stage focused inference for resource-constrained collision-free navigation. Proceedings of Robotics: Science and Systems, Rome, Italy, July 2015. PDF.
✽ John Leonard, Jonathan How, Seth Teller, Mitch Berger, Stefan Campbell, Gaston Fiore, Luke Fletcher, Emilio Frazzoli, Albert Huang, Sertac Karaman, Olivier Koch, Yoshiaki Kuwata, David Moore, Edwin Olson, Steve Peters, Justin Teo, Robert Truax, Matthew Walter, David Barrett, Alexander Epstein, Keoni Maheloni, Katy Moyer, Troy Jones, Ryan Buckley, Matthew Antone, Robert Galejs, Siddhartha Krishnamurthy, and Jonathan Williams. 2008. A perception-driven autonomous urban vehicle. Journal of Field Robotics 25:727–774. PDF.
✽ David M. Rosen, Charles DuHadway, and John J. Leonard. 2015. A convex relaxation for approximate global optimization in simultaneous localization and mapping. In Proceedings of the International Conference on Robotics and Automation (ICRA). PDF.
Brian Hayes. 2011. Leave the driving to it. American Scientist, 99:362-366. PDF.
Z. Josh Huang and Liqun Luo. 2015. It takes the world to understand the brain: International brain projects discuss how to coordinate efforts. Science 350:42–44. Abstract.
A. Paul Alivisatos, Miyoung Chun, George M. Church, Ralph J. Greenspan, Michael L. Roukes, and Rafael Yuste. 2012. The Brain Activity Map project and the challenge of functional connectomics. Neuron 74:970–974. Abstract.
Thomas R. Insel, Story C. Landis, and Francis S. Collins. 2013. The NIH BRAIN initiative. Science 340:687–688. Abstract.
Christof Koch and R. Clay Reid. 2012. Observatories of the mind. Nature 483:397–398. Abstract.
Martin Ford. 2013. Could artificial intelligence create an unemployment crisis? Communications of the ACM 56(7):37–39. Citation.
Natasha McCarthy. 2009. Autonomous Systems: Social, Legal and Ethical Issues. London: Royal Academy of Engineering. PDF.
Stuart Russell, Sabine Hauert, Russ Altman, and Manuela Veloso. 2015. Ethics of artificial intelligence. Nature 521:415–418. PDF.