1 citations · 1 across the 2 of their papers we have counts for
3 papers
Sparse Autoencoders for Interpretable Out-of-Distribution Detection
Ayush Karmacharya, Luke Luschwitz, Lucia Romero +2
Reliable detection of out-of-distribution (OOD) samples is crucial for the safe deployment of machine learning models. Neural networks often produce overconfident predictions for i…
Large Language Models for Financial Aid in Financial Time-series Forecasting
Md Khairul Islam, Ayush Karmacharya, Timothy Sue +1
Considering the difficulty of financial time series forecasting in financial aid, much of the current research focuses on leveraging big data analytics in financial services. One m…
Interpreting Time Series Transformer Models and Sensitivity Analysis of Population Age Groups to COVID-19 Infections
Md Khairul Islam, Tyler Valentine, Timothy Joowon Sue +5
Interpreting deep learning time series models is crucial in understanding the model's behavior and learning patterns from raw data for real-time decision-making. However, the compl…