Seminars

Sanja Fidler, Department of Computer Science, University of Toronto; and Director of AI, NVIDIA corporation Towards AI for 3D Content Creation 3D content is key in several domains such as architecture, film, gaming, and robotics. However, creating 3D content can be very time consuming -- the artists need to sculpt...

Ruslan Salakhutdinov, UPMC Professor of Computer Science, Department of Machine Learning, Carnegie Mellon University Integrating Domain-Knowledge into Deep Learning. In this talk I will first discuss deep learning models that can find semantically meaningful representations of words, learn to read documents and answer questions about their content. I will introduce...

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...

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...

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...

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 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...

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...

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...

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...