1 citations · 1 across the 6 of their papers we have counts for
6 papers
Fine-Grained Graph Generation through Latent Mixture Scheduling
Nidhi Vakil, Hadi Amiri
Structure aware graph generation aims to generate graphs that satisfy given topological properties. It has applications in domains such as drug discovery, social network modeling,…
MedDec: A Dataset for Extracting Medical Decisions from Discharge Summaries
Mohamed Elgaar, Jiali Cheng, Nidhi Vakil +2
Medical decisions directly impact individuals' health and well-being. Extracting decision spans from clinical notes plays a crucial role in understanding medical decision-making pr…
CogniVoice: Multimodal and Multilingual Fusion Networks for Mild Cognitive Impairment Assessment from Spontaneous Speech
Jiali Cheng, Mohamed Elgaar, Nidhi Vakil +1
Mild Cognitive Impairment (MCI) is a medical condition characterized by noticeable declines in memory and cognitive abilities, potentially affecting individual's daily activities.…
Complexity-Guided Curriculum Learning for Text Graphs
Nidhi Vakil, Hadi Amiri
Curriculum learning provides a systematic approach to training. It refines training progressively, tailors training to task requirements, and improves generalization through exposu…
Curriculum Learning for Graph Neural Networks: A Multiview Competence-based Approach
Nidhi Vakil, Hadi Amiri
A curriculum is a planned sequence of learning materials and an effective one can make learning efficient and effective for both humans and machines. Recent studies developed effec…
Generic and Trend-aware Curriculum Learning for Relation Extraction in Graph Neural Networks
Nidhi Vakil, Hadi Amiri
We present a generic and trend-aware curriculum learning approach for graph neural networks. It extends existing approaches by incorporating sample-level loss trends to better disc…