29 citations · 40 across the 8 of their papers we have counts for
8 papers
Multi-objective Deep Data Generation with Correlated Property Control
Shiyu Wang, Xiaojie Guo, Xuanyang Lin +11
Developing deep generative models has been an emerging field due to the ability to model and generate complex data for various purposes, such as image synthesis and molecular desig…
Multiple Instance Learning for Detecting Anomalies over Sequential Real-World Datasets
Parastoo Kamranfar, David Lattanzi, Amarda Shehu +1
Detecting anomalies over real-world datasets remains a challenging task. Data annotation is an intensive human labor problem, particularly in sequential datasets, where the start a…
Interpretable Molecular Graph Generation via Monotonic Constraints
Yuanqi Du, Xiaojie Guo, Amarda Shehu +1
Designing molecules with specific properties is a long-lasting research problem and is central to advancing crucial domains such as drug discovery and material science. Recent adva…
Traffic Flow Forecasting with Maintenance Downtime via Multi-Channel Attention-Based Spatio-Temporal Graph Convolutional Networks
Yuanjie Lu, Parastoo Kamranfar, David Lattanzi +1
Forecasting traffic flows is a central task in intelligent transportation system management. Graph structures have shown promise as a modeling framework, with recent advances in sp…
Space Partitioning and Regression Mode Seeking via a Mean-Shift-Inspired Algorithm
Wanli Qiao, Amarda Shehu
The mean shift (MS) algorithm is a nonparametric method used to cluster sample points and find the local modes of kernel density estimates, using an idea based on iterative gradien…
Decoy Selection for Protein Structure Prediction Via Extreme Gradient Boosting and Ranking
Nasrin Akhter, Gopinath Chennupati, Hristo Djidjev +1
Identifying one or more biologically-active/native decoys from millions of non-native decoys is one of the major challenges in computational structural biology. The extreme lack of…