29 citations · 56 across the 16 of their papers we have counts for
4 papers · 1 filter
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…
Transformer Neural Networks Attending to Both Sequence and Structure for Protein Prediction Tasks
Anowarul Kabir, Amarda Shehu
The increasing number of protein sequences decoded from genomes is opening up new avenues of research on linking protein sequence to function with transformer neural networks. Rece…
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…