Research Focus: Week of October 7, 2024
Simplifying secure decision tree training; Improving accuracy of audio content detection; A novel neurosymbolic system for converting text to tables; New video series: AI for Business Transformation; TEE security protections for container workloads.
MICON (Molecular-Image Contrastive Learning)
This is the repository for paper “Causal integration of chemical structures in self-supervised learning improves representations of microscopy images for morphological profiling”. Learning effective representations of cells in microscopy images can fuel many applications. Here,…
ProtNote: a multimodal method for protein-function annotation
ProtNote is a multimodal deep learning model that leverages free-form text to enable both supervised and zero-shot protein function prediction.
Stress-testing biomedical vision models with RadEdit: A synthetic data approach for robust model deployment
RadEdit stress-tests biomedical vision models by simulating dataset shifts through precise image editing. It uses diffusion models to create realistic, synthetic datasets, helping to identify model weaknesses and evaluate robustness.
AI for Business Transformation: Multimodal Models
Multimodal models hold the key to unprecedented advances in AI, moving beyond text and numbers to incorporate a much wider spectrum of inputs. AI research leaders Peter Lee and Vijay Mital discuss how researchers are…