44 citations · 240 across the 10 of their papers we have counts for
11 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…
Hawkes Processes with Stochastic Excitations
Young Lee, Kar Wai Lim, Cheng Soon Ong
We propose an extension to Hawkes processes by treating the levels of self-excitation as a stochastic differential equation. Our new point process allows better approximation in ap…
Bibliographic Analysis with the Citation Network Topic Model
Kar Wai Lim, Wray Buntine
Bibliographic analysis considers author's research areas, the citation network and paper content among other things. In this paper, we combine these three in a topic model that pro…
Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling
Kar Wai Lim, Changyou Chen, Wray Buntine
Twitter data is extremely noisy -- each tweet is short, unstructured and with informal language, a challenge for current topic modeling. On the other hand, tweets are accompanied b…
Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes
Kar Wai Lim, Wray Buntine, Changyou Chen +1
The Dirichlet process and its extension, the Pitman-Yor process, are stochastic processes that take probability distributions as a parameter. These processes can be stacked up to f…
Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon
Kar Wai Lim, Wray Buntine
Aspect-based opinion mining is widely applied to review data to aggregate or summarize opinions of a product, and the current state-of-the-art is achieved with Latent Dirichlet All…
On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off
Kar Wai Lim, Scott Sanner, Shengbo Guo
It has been previously noted that optimization of the n-call@k relevance objective (i.e., a set-based objective that is 1 if at least n documents in a set of k are relevant, otherw…
Bibliographic Analysis on Research Publications using Authors, Categorical Labels and the Citation Network
Kar Wai Lim, Wray Buntine
Bibliographic analysis considers the author's research areas, the citation network and the paper content among other things. In this paper, we combine these three in a topic model…