interpretability 1neural networks 1out-of-distribution detection 1representation learning 1sparse autoencoders 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.LG2026
Sparse Autoencoders for Interpretable Out-of-Distribution Detection
Ayush Karmacharya, Luke Luschwitz, Lucia Romero +2
The paper proposes using sparse autoencoders to extract interpretable sparse features from intermediate neural network layers and defines an OOD detection score based on cosine sim…
cs.LG2024
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…