APPM Department Colloquium - Colin Raffel

March 19, 2021

Colin Raffel; Assistant Professor of Computer Science; University of North Carolina, Chapel Hill; and Staff Research Scientist, Google Brain T5 and large language models: The good, the bad, and the ugly T5 and other large pre-trained language models have proven to be a crucial component of the modern natural language...

APPM Department Colloquium - Stephen Kissler

March 17, 2021

Stephen Kissler, Postdoctoral Fellow at Harvard T.H. Chan School of Public Health SARS-CoV-2 across scales Mathematical models have provided key insights into SARS-CoV-2 dynamics at the global, local, and physiological scales. I will summarize some of our research efforts within each of these contexts. Early in the pandemic, a deterministic...

APPM Recruitment Colloquium - Adrianna Gillman and Francois Meyer

March 12, 2021

Adrianna Gillman, Department of Applied Mathematics, University of Colorado Boulder Fast algorithms group: Accurate, efficient and robust techniques for solving partial differential equations Partial differential equations are often used to model physical phenomena. Unfortunately, it is impossible to simply write down the solution to most of the equations. Instead we...

APPM and AWM Joint Colloquium - Marsha Berger

March 12, 2021

Marsha Berger; Silver Professor of Computer Science and Mathematics; Courant Institute of Mathematical Sciences, New York University Computing Fluid Flows in Complex Geometry We give an overview of the difficulties in simulating fluid flow in complex geometry. The principal approaches use either overlapping or patched body-fitted grdis, unstructured grids, or...

APPM Department Colloquium - Joan Bruna

March 5, 2021

APPM Department Colloquium - Joan Bruna Joan Bruna; Assistant Professor; Courant Institute of Mathematical Sciences, New York University Mathematical aspects of neural network approximation and learning High-dimensional learning remains an outstanding phenomena where experimental evidence outpaces our current mathematical understanding, mostly due to the recent empirical successes of Deep Learning...

APPM Department Colloquium - Dumitru Erhan

March 1, 2021

Dumitru Erhan, Staff Research Scientist and Tech Lead Manager, Google Brain Enabling world models via unsupervised representation learning of environments. In order to build intelligent agents that quickly adapt to new scenes, conditions, tasks, we need to develop techniques, algorithms and models that can operate on little data or that...

APPM Department Colloquium - Mingxing Tan

Feb. 26, 2021

Mingxing Tan, Staff Software Engineer, Google Brain AutoML for Efficient Vision Learning This talk will focus on a few recent progresses we have made on AutoML, particularly on neural architecture search for efficient convolutional neural networks. We will first discuss the challenges and solutions in designing network architecture search spaces...

APPM Department Colloquium - Kalesha Bullard

Feb. 26, 2021

Kalesha Bullard, Postdoctoral Researcher, Facebook AI Research Learning through Interaction in Cooperative Multi-Agent Systems Effective communication is an important skill for enabling information exchange and cooperation in multi-agent systems, in which agents coexist in a shared environment with humans and/or other artificial agents. Indeed, human domain experts can be a...

Joint APPM/PHYS Colloquium - Philip Stark

Feb. 24, 2021

Philip Stark; Department of Statistics; University of California, Berkeley Evidence-Based Elections Elections rely on people, hardware, and software, all of which are fallible and subject to manipulation. Well resourced nation-states continue to attack U.S. elections. Voting equipment is built by private vendors–some foreign, but all using foreign parts. Many states...

APPM Department Colloquium - Jeffrey Pennington

Feb. 19, 2021

Jeffrey Pennington, Research Scientist, Google Brain Demystifying deep learning through high-dimensional statistics As deep learning continues to amass ever more practical success, its novelty has slowly faded, but a sense of mystery persists and we still lack satisfying explanations for how and why these models perform so well. Among the...

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