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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 me
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Posts
AdvFlow: Black-box Adversarial Attacks using Normalizing Flows
Published:
A quick overview of our NeurIPS 2020 paper.
Linear Rational Spline Flows
Published:
A quick overview of normalizing flows, coupling layers, and our AISTATS 2020 paper.
Denoising Diffusion Probabilistic Models
Published:
Brief introduction to diffusion models used in the Denoising Diffusion Probabilistic Models by Ho et al.
portfolio
Portfolio item number 1
Published:
Short description of portfolio item number 1
Portfolio item number 2
Published:
Short description of portfolio item number 2
publications
A Sampling Theorem for Convex Shapes with Algebraic Boundaries
Published in International Conference on Sampling Theory and Applications (SampTA), 2017
In this paper we present a sampling result about continuous-domain black and white images that form a convex shape.
Deterministic Design of Toeplitz Matrices With Small Coherence Based on Weyl Sums
Published in IEEE Signal Processing Letters, 2019
This paper is about designing Toeplitz measurement matrices based on Weyl sums.
Invertible Generative Modeling using Linear Rational Splines
Published in The 23rd International Conference on Artifcial Intelligence and Statistics (AISTATS), 2020
In this paper, we explore using linear rational splines as an invertible transformations for normalizing flows.
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows
Published in The 34th Conference on Neural Information Processing Systems (NeurIPS), 2020
In this paper, we propose a novel black-box adversarial attack that exploits clean data distribution to conceal itself.
ℓ∞-Robustness and Beyond: Unleashing Efficient Adversarial Training
Published in The 17th European Conference on Computer Vision (ECCV), 2022
In this work, we reduce the training time of adversarial training using adaptive sample selection.
COLLIDER: A Robust Training Framework for Backdoor Data
Published in The 16th Asian Conference on Computer Vision (ACCV), 2022
In this paper, we utilize adaptive subset selection to eliminate backdoor data and train a clean model.
Adversarial Coreset Selection for Efficient Robust Training
Published in Preprint, 2022
In this paper, we theoretically analyze adversarial coreset selection and provide insights into its working dynamics.
The Devil’s Advocate: Shattering the Illusion of Unexploitable Data using Diffusion Models
Published in Preprint, 2023
In this work, we reveal the fragility of unlearnable examples using diffusion models.
talks
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.