Upcoming Events

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Events Archive

Deep Learning is Not So Mysterious or Different

Hosted by the Princeton Astro Data Lab
Prof. Peter Melchior

Deep neural networks are often seen as different from other model classes by defying conventional notions of generalization. Popular examples of anomalous generalization behaviour include benign overfitting, double descent, and the success of…

Location
Lewis Library 138
Speaker
New Frontiers in Fusion Energy Enabled by AI and High Performance Computing - Honoring Professor William Tang's Scientific Accomplishments

Join us for the symposium “New Frontiers in Fusion Energy Enabled by AI and High-Performance Computing - Honoring the Scientific Accomplishments of Professor William Tang” as we celebrate the groundbreaking contributions of Professor William Tang. A visionary in the integration of theoretical physics with computational science,…

Location
138 Lewis Science Library
With enough data and the right algorithms is your future predictable? Some evidence from LLMs and complete population-scale data

Lunch is available beginning at 12 PM

Speaker to begin promptly at 12:30 PM

Abstract: How predictable are life trajectories? How much can predictability be improved with more data and better algorithms?  What are the sources of inherent unpredictability that seem impossible to overcome in the foreseeable…

Location
Bendheim House 103
Speaker
From Genome to Theorem: Can Large Language Models Do Science?

Lunch is available beginning at 12 PM

Speaker to begin promptly at 12:30 PM

Co-sponsored by AI2 and the Center for Statistics and Machine Learning

Contributions to and/or sponsorship of any event does not constitute departmental or institutional endorsement of the specific program, speakers or views presented.

Location
Bendheim House 103
Speaker
Replication for Language Models Problems, Principles, and Best Practice for Political Science

Lunch is available beginning at 12 PM

Speaker to begin promptly at 12:30 PM

Abstract: Excitement about Large Language Models (LMs) abounds. These tools require minimal researcher input and yet make it possible to annotate and generate large quantities of data. While LMs are promising, there has been almost no…

Location
Bendheim House 103
Speaker
Cracking the Market Code: Building Large Foundation Models for High-Frequency Trading

Lunch is available beginning at 12 PM

Speaker to begin promptly at 12:30 PM

Co-sponsored by AI2 and the Center for Statistics and Machine Learning

Abstract: In this talk, I will delve into the exciting research opportunities and unique challenges of building large foundation models for high…

Location
Bendheim House 103
Speaker
Self-Supervised Reinforcement Learning: Some Surprises and Open Problems

Lunch is available beginning at 12 PM

Speaker to begin promptly at 12:30 PM

Abstract: TBD

Contributions to and/or sponsorship of any event does not constitute departmental or institutional endorsement of the specific program, speakers or views presented.

Location
Bendheim House 103
Speaker
What does Generative AI Mean for the Hardware that has to Ultimately Run It?

Lunch is available beginning at 12 PM

Speaker to begin promptly at 12:30 PM

Abstract: Generative AI has the potential to transform the efficiency of critical processes in broad domains, ranging from healthcare, to education, to logistics. However, such transformations require holistic integration of AI systems…

Location
Bendheim House 103
Speaker
Machine Learning In Data Assimilation

Co-sponsored by PACM and the Center for Statistics and Machine Learning

Abstract: 

Data assimilation refers to a particular class of inverse problems in which the unknown parameter is the initial condition, or entire solution trajectory, of a (possibly stochastic) dynamical system. The data comprises…

Location
214 Fine Hall
Speaker