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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About
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Posts
The Lagrangian Dual
Published:
Important: This blog is rather long because I go into detail over an example. You are recommened to skip the proofs if they are too obivious or not relevant to you.
GSOC21 Highlights
Published:
Important: Many blogs discuss how to write a successful proposal for GSOC, but this isn’t one of them. This blog talks about my GSOC experience, and I will link below to blogs that talk a bit about how to write a successful proposal that I agree with or used when I was crafting mine.
Non Linear Programming : A Primer
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Deprecation Warning: This was from a previous github blog and as such there might be some formating issues from that previous blog post that I have not addressed from that time
N-interacting Particles
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Deprecation Warning: This was from a previous github blog and as such there might be some formating issues from that previous blog post that I have not addressed from that time
portfolio
Portfolio item number 1
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Short description of portfolio item number 1
Portfolio item number 2
Published:
Short description of portfolio item number 2
publications
Natural Gradients
Published in , 2020
This report is a survey on natural gradients
Recommended citation: M.L.Ang Natural Gradients, 2021 http://neoanarika.github.io/files/MA4270_Project___Natural_Gradients.pdf
Refining Deep Generative Models via Discriminator Gradient Flow
Published in International Conference on Learning Representations (ICLR), 2021
This paper is about refining samples from deep generative models using discriminator gradient flows.
Recommended citation: A.F.Ansari, M.L.Ang, and H.Soh. Refining deep generative models via discriminator gradient flow.In International Conference on Learning Representations, 2021. https://arxiv.org/abs/2012.00780
Thompson Sampling for Gaussian Entropic Risk Bandits
Published in , 2021
This paper is about extending my friend Joel Chang work to entropic bandits for a class
Recommended citation: Ang, Ming Liang, Eloise YY Lim, and Joel QL Chang. "Thompson Sampling for Gaussian Entropic Risk Bandits." arXiv preprint arXiv:2105.06960 (2021). https://arxiv.org/abs/2105.06960
Using Deep Generative Priors For Inverse Problems And Bayesian Optimisation
Published in , 2021
This paper is about using generative modelling to solve inverse problems
Recommended citation: ML Ang Using Deep Generative Priors For Inverse Problems And Bayesian Optimisation 2021 Ang_Ming_Liang_Jonathan_Scarlett_report (2).pdf
talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.