Machine Learning and Friends Lunch
Machine Learning and Friends Lunch: Boqing Gong, From Domain Adaptation to VideoPrism: A Decade-Long Quest for Out-of-Domain Visual Generalization
This talk explores the challenges of out-of domain (OOD) generalization in computer vision, encompassing tasks like domain adaptation.
Machine Learning and Friends Lunch: Chen Sun, Grounding Deep Generative Models in the Physical World
Machine Learning and Friends Lunch
Machine Learning and Friends Lunch: Sherry Yang, Learning World Models and Agents for High-Cost Environments
Machine Learning and Friends Lunch featuring Sherry Yang, Assistant Professor of Computer Science at NYU Courant and
a scientist at Google DeepMind.
Machine Learning and Friends Lunch: Claudia Shi, Novel Problems, Classic Solutions: Understanding LLMs Through the Lens of Statistics
In this talk, Shi will present two recent projects that use statistical methods to deepen our understanding of LLMs.
Machine Learning and Friends Lunch: Wei-Chiu Ma, Towards Physically-Grounded Digital Twins and Beyond
Machine Learning and Friends Lunch featuring Wei-Chiu Ma, an Assistant Professor of Computer Science at Cornell
University.
Machine Learning and Friends Lunch: Alex Wong, The Know-How of Multimodal Depth Perception
Training deep neural networks requires tens of thousands to millions of examples, so curating multimodal vision datasets amounts to numerous man-hours.
Machine Learning and Friends Lunch: Andrew Wu, Marabou 2.0: A Versatile Formal Analyzer of Neural Networks
Join Andrew Wu for a presentation on version 2.0 of Marabou, a toolkit for formally verifying user-defined properties on deep neural networks.
Machine Learning and Friends Lunch: Michael Boratko, Representational Capacity of Vector Embeddings for Retrieval
Machine Learning and Friends Lunch featuring Michael Boratko, a research scientist at Google DeepMind.