Search Results for author:
Found 5 papers, 2 papers with code
Decoding In-Context Learning: Neuroscience-inspired Analysis of Representations in Large Language Models
In this work, we investigate how LLM embeddings and attention representations change following in-context-learning, and how these changes mediate improvement in behavior.
Streaming Active Learning with Deep Neural Networks
Active learning is perhaps most naturally posed as an online learning problem.
Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting
Most of the prior work relied on modeling pollutant concentrations collected from ground-based monitors and meteorological data for long-term forecasting of outdoor ozone, oxides of nitrogen, and PM2. 5.
Learning Genomic Representations to Predict Clinical Outcomes in Cancer
Genomics are rapidly transforming medical practice and basic biomedical research, providing insights into disease mechanisms and improving therapeutic strategies, particularly in cancer.
A Continuous-time Mutually-Exciting Point Process Framework for Prioritizing Events in Social Media
In our experiments, we demonstrate that our algorithm is able to achieve the-state-of-the-art performance in terms of analyzing, predicting, and prioritizing events.
