15 citations · 73 across the 24 of their papers we have counts for
6 papers · 1 filter
Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection
Liangqi Yuan, Dong-Jun Han, Su Wang +2
Multimodal federated learning (MFL) aims to enrich model training in FL settings where clients are collecting measurements across multiple modalities. However, key challenges to MF…
Stochastic Deep Koopman Model for Quality Propagation Analysis in Multistage Manufacturing Systems
Zhiyi Chen, Harshal Maske, Huanyi Shui +6
The modeling of multistage manufacturing systems (MMSs) has attracted increased attention from both academia and industry. Recent advancements in deep learning methods provide an o…
Targeted collapse regularized autoencoder for anomaly detection: black hole at the center
Amin Ghafourian, Huanyi Shui, Devesh Upadhyay +3
Autoencoders have been extensively used in the development of recent anomaly detection techniques. The premise of their application is based on the notion that after training the a…
Model Monitoring and Robustness of In-Use Machine Learning Models: Quantifying Data Distribution Shifts Using Population Stability Index
Aria Khademi, Michael Hopka, Devesh Upadhyay
Safety goes first. Meeting and maintaining industry safety standards for robustness of artificial intelligence (AI) and machine learning (ML) models require continuous monitoring f…
BTranspose: Bottleneck Transformers for Human Pose Estimation with Self-Supervised Pre-Training
Kaushik Balakrishnan, Devesh Upadhyay
The task of 2D human pose estimation is challenging as the number of keypoints is typically large (~ 17) and this necessitates the use of robust neural network architectures and tr…
Stochastic Adversarial Koopman Model for Dynamical Systems
Kaushik Balakrishnan, Devesh Upadhyay
Dynamical systems are ubiquitous and are often modeled using a non-linear system of governing equations. Numerical solution procedures for many dynamical systems have existed for s…