4 citations · 4 across the 1 of their papers we have counts for
4 papers
Explaining Chemical Toxicity using Missing Features
Kar Wai Lim, Bhanushee Sharma, Payel Das +2
Chemical toxicity prediction using machine learning is important in drug development to reduce repeated animal and human testing, thus saving cost and time. It is highly recommende…
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Vijil Chenthamarakshan, Payel Das, Samuel C. Hoffman +8
The novel nature of SARS-CoV-2 calls for the development of efficient de novo drug design approaches. In this study, we propose an end-to-end framework, named CogMol (Controlled Ge…
GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection
Quoc Phong Nguyen, Kar Wai Lim, Dinil Mon Divakaran +2
This paper looks into the problem of detecting network anomalies by analyzing NetFlow records. While many previous works have used statistical models and machine learning technique…
Simulation and Calibration of a Fully Bayesian Marked Multidimensional Hawkes Process with Dissimilar Decays
Kar Wai Lim, Young Lee, Leif Hanlen +1
We propose a simulation method for multidimensional Hawkes processes based on superposition theory of point processes. This formulation allows us to design efficient simulations fo…