Search Results for author: Ruoxi Sun

Found 18 papers, 8 papers with code

Neural Spline Search for Quantile Probabilistic Modeling

no code implementations12 Jan 2023 Ruoxi Sun, Chun-Liang Li, Sercan O. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister

Accurate estimation of output quantiles is crucial in many use cases, where it is desired to model the range of possibility.

regression Time Series Forecasting

The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram Matrices

1 code implementation23 Sep 2022 Wanlun Ma, Derui Wang, Ruoxi Sun, Minhui Xue, Sheng Wen, Yang Xiang

However, recent advanced backdoor attacks show that this assumption is no longer valid in dynamic backdoors where the triggers vary from input to input, thereby defeating the existing defenses.

M^4I: Multi-modal Models Membership Inference

1 code implementation15 Sep 2022 Pingyi Hu, Zihan Wang, Ruoxi Sun, Hu Wang, Minhui Xue

To achieve this, we propose Multi-modal Models Membership Inference (M^4I) with two attack methods to infer the membership status, named metric-based (MB) M^4I and feature-based (FB) M^4I, respectively.

Image Captioning Inference Attack +2

Does GNN Pretraining Help Molecular Representation?

no code implementations13 Jul 2022 Ruoxi Sun, Hanjun Dai, Adams Wei Yu

Extracting informative representations of molecules using Graph neural networks (GNNs) is crucial in AI-driven drug discovery.

Drug Discovery

StyleFool: Fooling Video Classification Systems via Style Transfer

1 code implementation30 Mar 2022 Yuxin Cao, Xi Xiao, Ruoxi Sun, Derui Wang, Minhui Xue, Sheng Wen

In this paper, we focus on unrestricted perturbations and propose StyleFool, a black-box video adversarial attack via style transfer to fool the video classification system.

Adversarial Attack Classification +3

PublicCheck: Public Integrity Verification for Services of Run-time Deep Models

no code implementations21 Mar 2022 Shuo Wang, Sharif Abuadbba, Sidharth Agarwal, Kristen Moore, Ruoxi Sun, Minhui Xue, Surya Nepal, Seyit Camtepe, Salil Kanhere

Existing integrity verification approaches for deep models are designed for private verification (i. e., assuming the service provider is honest, with white-box access to model parameters).

Model Compression

Learning to Prompt for Continual Learning

1 code implementation CVPR 2022 Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, Tomas Pfister

The mainstream paradigm behind continual learning has been to adapt the model parameters to non-stationary data distributions, where catastrophic forgetting is the central challenge.

Continual Learning Image Classification

Towards understanding retrosynthesis by energy-based models

no code implementations NeurIPS 2021 Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai

In this paper, we propose a framework that unifies sequence- and graph-based methods as energy-based models (EBMs) with different energy functions.

Drug Discovery

Measuring Vulnerabilities of Malware Detectors with Explainability-Guided Evasion Attacks

no code implementations19 Nov 2021 Ruoxi Sun, Wei Wang, Tian Dong, Shaofeng Li, Minhui Xue, Gareth Tyson, Haojin Zhu, Mingyu Guo, Surya Nepal

We find that (i) commercial antivirus engines are vulnerable to AMM-guided manipulated samples; (ii) the ability of a manipulated malware generated using one detector to evade detection by another detector (i. e., transferability) depends on the overlap of features with large AMM values between the different detectors; and (iii) AMM values effectively measure the importance of features and explain the ability to evade detection.

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography

no code implementations20 Jul 2021 Zihan Wang, Olivia Byrnes, Hu Wang, Ruoxi Sun, Congbo Ma, Huaming Chen, Qi Wu, Minhui Xue

Data hiding is the process of embedding information into a noise-tolerant signal such as a piece of audio, video, or an image, including Digital Watermarking for robust identity verification and Steganography to embed data for the purpose of secure and secret communication.

Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics

1 code implementation17 Sep 2020 Li Li, Stephan Hoyer, Ryan Pederson, Ruoxi Sun, Ekin D. Cubuk, Patrick Riley, Kieron Burke

Including prior knowledge is important for effective machine learning models in physics, and is usually achieved by explicitly adding loss terms or constraints on model architectures.

BIG-bench Machine Learning

Energy-based View of Retrosynthesis

no code implementations14 Jul 2020 Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai

Retrosynthesis -- the process of identifying a set of reactants to synthesize a target molecule -- is of vital importance to material design and drug discovery.

Drug Discovery Single-step retrosynthesis

Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models

no code implementations NeurIPS 2019 Ruoxi Sun, Ian Kinsella, Scott Linderman, Liam Paninski

However, current sensors and imaging approaches still face significant limitations in SNR and sampling frequency; therefore statistical denoising and interpolation methods remain critical for understanding single-trial spatiotemporal dendritic voltage dynamics.

Bayesian Inference Denoising

Scalable approximate Bayesian inference for particle tracking data

1 code implementation ICML 2018 Ruoxi Sun, Liam Paninski

This approach is therefore highly flexible and improves on the state of the art in terms of accuracy; provides uncertainty estimates about the particle locations and identities; and has a test run-time that scales linearly as a function of the data length and number of particles, thus enabling Bayesian inference in arbitrarily large particle tracking datasets.

Bayesian Inference

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