The in-person open house will allow admitted students to tour the Yale campus, visit our research facilities, and meet with Yale faculty, staff, graduate students, and other incoming students such as yourself. For more information on visiting in person, see the guidelines before registering.
The in-person open house will allow admitted students to tour the Yale campus, visit our research facilities, and meet with Yale faculty, staff, graduate students, and other incoming students such as yourself. For more information on visiting in person, see the guidelines before registering.
Built by the US government to house the Hanford nuclear site workers who manufactured weapons-grade plutonium for the Manhattan Project, Richland, Washington is proud of its heritage as a nuclear company town and proud of the atomic bomb it helped create. RICHLAND offers a prismatic, placemaking portrait of a community staking its identity and future on its nuclear origin story, presenting a timely examination of the habits of thought that normalize the extraordinary violence of the past.
Building upon two decades of edge-finding archaeological research, the Yale Ancient Pharmacology Program continues to refine a transdisciplinary approach that seamlessly blends ethnography, materiality, and technology. Nucleating at the Yale Peabody Museum has allowed YAPP to work across its divisions and vast collections to push our knowledge of ancient organic materials through the fusion of ethnohistory, phytochemistry, and data science.
Classical models of inference, such as those based on logic, take inference to be *conceptual* – i.e., to involve representations formed of terms, predicates, relation symbols, and the like. Conceptual representation of this sort is assumed to reflect the structure of the world: objects of various types, exemplifying properties, standing in relations, grouped together in sets, etc. These paired roughly algebraic assumptions (one epistemic, the other ontological) form the basis of classical logic and traditional AI (GOFAI).
In this talk, Professor Paseau will describe some of his work on inference within mathematics and more generally. Inferences can be usefully divided into deductive or non-deductive. Formal logic studies deductive inference, the obvious question here being: which formal logic correctly captures it? His view, defended in his recent monograph One True Logic (Oxford UP, co-authored with Owen Griffiths), is that any such logic must be highly infinite. In this Inference Project event, he shall explain what this means and sketch some arguments for it.
An ambitious, rock-climbing geology student defies her imperious advisor to travel to the Nevada high desert, where a career-defining discovery and an unexpected friendship with a young cattle rancher force her to make life-altering decisions. Unconformity is the story of a friendship tested in the American West, framed by geology, rock climbing, land rights, exploitation in academia, and the climate crisis.
Join us for a post-film moderated conversation with writer and director Jonathan DiMaio ‘09.
In Life’s Edge, Carl Zimmer explores the nature of life and investigates why scientists have struggled to draw its boundaries. He handles pythons, goes spelunking to visit hibernating bats, and even tries his hand at evolution. Zimmer visits scientists making miniature human brains to ask when life begins, and follows a voyage that delivered microscopic animals to the moon, where they now exist in a state between life and death. From the coronavirus to consciousness, Zimmer demonstrates that biology, for all its advances, has yet to achieve its greatest triumph: a full theory of life.
The sciences are replete with high-fidelity simulators: computational manifestations of causal, mechanistic models. Ironically, while these simulators provide our highest-fidelity physical models, they are not well suited for inferring properties of the model from data. Professor Kyle Cranmer of New York University will describe the emerging area of simulation-based inference and describe how machine learning is being brought to bear on these challenging problems.
Mariano Sigman is one of the most outstanding neuroscientists in the world, with over 150 publications in the most prestigious scientific journals. He is also passionate about experimentation and has worked with magicians, chess masters, musicians, athletes and visual artists to bring his knowledge of neuroscience to different aspects of human culture and apply it in different contexts. He has participated twice (2016 and 2017) in the TED global events in Vancouver, the second with Dan Ariely.
