Large multimodal datasets have been instrumental in recent breakthroughs...
Multimodal learning is defined as learning over multiple heterogeneous i...
Self supervision and natural language supervision have emerged as two
ex...
Contrastively trained image-text models such as CLIP, ALIGN, and BASIC h...
For machine learning systems to be reliable, we must understand their
pe...
Recent work has shown that the performance of machine learning models ca...
Combining satellite imagery with machine learning (SIML) has the potenti...
We study how robust current ImageNet models are to distribution shifts
a...
We investigate the connections between neural networks and simple buildi...
Inexpensive cloud services, such as serverless computing, are often
vuln...
We introduce a systematic framework for quantifying the robustness of
cl...
Serverless cloud computing handles virtually all the system administrati...
Linear algebra operations are widely used in scientific computing and ma...
Machine learning is currently dominated by largely experimental work foc...
In this project, we build a modular, scalable system that can collect, s...
The precise physical process that triggers solar flares is not currently...