Search Results for author: Kar Wai Lim

Found 10 papers, 1 papers with code

Explaining Chemical Toxicity using Missing Features

no code implementations23 Sep 2020 Kar Wai Lim, Bhanushee Sharma, Payel Das, Vijil Chenthamarakshan, Jonathan S. Dordick

Chemical toxicity prediction using machine learning is important in drug development to reduce repeated animal and human testing, thus saving cost and time.

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models

no code implementations NeurIPS 2020 Vijil Chenthamarakshan, Payel Das, Samuel C. Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic

CogMol also includes insilico screening for assessing toxicity of parent molecules and their metabolites with a multi-task toxicity classifier, synthetic feasibility with a chemical retrosynthesis predictor, and target structure binding with docking simulations.

Simulation and Calibration of a Fully Bayesian Marked Multidimensional Hawkes Process with Dissimilar Decays

no code implementations13 Mar 2018 Kar Wai Lim, Young Lee, Leif Hanlen, Hongbiao Zhao

We propose a simulation method for multidimensional Hawkes processes based on superposition theory of point processes.

Point Processes

Hawkes Processes with Stochastic Excitations

no code implementations22 Sep 2016 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.

Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling

no code implementations22 Sep 2016 Kar Wai Lim, Changyou Chen, Wray Buntine

Exploiting this additional information, we propose the Twitter-Network (TN) topic model to jointly model the text and the social network in a full Bayesian nonparametric way.

Topic Models

Bibliographic Analysis with the Citation Network Topic Model

no code implementations22 Sep 2016 Kar Wai Lim, Wray Buntine

Bibliographic analysis considers author's research areas, the citation network and paper content among other things.

Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes

no code implementations22 Sep 2016 Kar Wai Lim, Wray Buntine, Changyou Chen, Lan Du

In this article, we present efficient methods for the use of these processes in this hierarchical context, and apply them to latent variable models for text analytics.

Topic Models

Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon

no code implementations21 Sep 2016 Kar Wai Lim, Wray Buntine

Although social media data like tweets are laden with opinions, their "dirty" nature (as natural language) has discouraged researchers from applying LDA-based opinion model for product review mining.

Opinion Mining Sentiment Analysis

Bibliographic Analysis on Research Publications using Authors, Categorical Labels and the Citation Network

no code implementations21 Sep 2016 Kar Wai Lim, Wray Buntine

In this paper, we combine these three in a topic model that produces a bibliographic model of authors, topics and documents, using a nonparametric extension of a combination of the Poisson mixed-topic link model and the author-topic model.

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