5 papers
ConformalHDC: Uncertainty-Aware Hyperdimensional Computing with Application to Neural Decoding
Ziyi Liang, Hamed Poursiami, Zhishun Yang +5
Hyperdimensional Computing (HDC) offers a computationally efficient paradigm for neuromorphic learning. Yet, it lacks rigorous uncertainty quantification, leading to open decision…
Heterogeneous Graph Alignment for Joint Reasoning and Interpretability
Zahra Moslemi, Ziyi Liang, Norbert Fortin +1
Multi-graph learning is crucial for extracting meaningful signals from collections of heterogeneous graphs. However, effectively integrating information across graphs with differin…
Weakly-Supervised Multimodal Learning on MIMIC-CXR
Andrea Agostini, Daphné Chopard, Yang Meng +5
Multimodal data integration and label scarcity pose significant challenges for machine learning in medical settings. To address these issues, we conduct an in-depth evaluation of t…
Optimal Transport for Latent Integration with An Application to Heterogeneous Neuronal Activity Data
Yubai Yuan, Babak Shahbaba, Norbert Fortin +3
Detecting dynamic patterns of task-specific responses shared across heterogeneous datasets is an essential and challenging problem in many scientific applications in medical scienc…
Unity by Diversity: Improved Representation Learning in Multimodal VAEs
Thomas M. Sutter, Yang Meng, Andrea Agostini +5
Variational Autoencoders for multimodal data hold promise for many tasks in data analysis, such as representation learning, conditional generation, and imputation. Current architec…