Selected Publications:

Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness [paper]
Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi
Available on arXiv.

Bounding Singular Values of Convolution Layers [paper] [code]
Sahil Singla, Soheil Feizi
Available on arXiv.

Adversarial Robustness of Flow-Based Generative Models [paper]
Phillip Pope, Yogesh Balaji, Soheil Feizi
AISTATS 2020.

Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks [paper] [code]
Alexander Levine, Soheil Feizi
AISTATS 2020.

Second-Order Group Influence Functions for Black-Box Predictions [paper]
Samyadeep Basu, Xuchen You, Soheil Feizi
Available on arXiv.

Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation [paper] [code]
Alexander Levine, Soheil Feizi
AAAI 2020

Adversarially Robust Distillation [paper]
Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein
AAAI 2020.

Maximum Likelihood Latent Space Embedding of Logistic Random Dot Product Graphs [paper] [code]
Luke O'Connor, Muriel Medard, Soheil Feizi
AAAI 2020

Functional Adversarial Attacks [paper] [code]
Cassidy Laidlaw, Soheil Feizi
NeurIPS, 2019.

Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks [paper] [code]
A. Ismail, M. Gunady, L. Pessoa, H. Bravo, S. Feizi
NeurIPS, 2019.

Quantum Wasserstein GANs [paper]
S. Chakrabarti, H. Yiming. T. Li, S. Feizi, X.Wu
NeurIPS, 2019.

Normalized Wasserstein Distance for Mixture Distributions with Applications in Adversarial Learning and Domain Adaptation [paper] [code]
Yogesh Balaji, Rama Chellappa, and Soheil Feizi
ICCV, 2019.

Certifiably Robust Interpretation in Deep Learning [paper]
Alexander Levine, Sahil Singla, Soheil Feizi
Available on arXiv.

Interpretable Adversarial Training for Text [paper]
Samuel Barham, Soheil Feizi
Available on arXiv.

Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation [paper] [code]
Sahil Singla, Eric Wallace, Shi Feng, Soheil Feizi
ICML, 2019.

Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs [paper] [code]
Yogesh Balaji, Hamed Hassani, Rama Chellappa, and Soheil Feizi
ICML, 2019.

Are adversarial examples inevitable? [paper]
Ali Shafahi, W. Ronny Huang, Christoph Studer, Soheil Feizi, Tom Goldstein
ICLR, 2019.

Robustness Certificates Against Adversarial Examples for ReLU Networks [paper]
Sahil Singla and Soheil Feizi
Available on arXiv.

Compressing GANs using Knowledge Distillation [paper]
Angeline Aguinaldo, Ping-Yeh Chiang, Alex Gain, Ameya Patil, Kolten Pearson, Soheil Feizi
Available on arXiv.

Porcupine Neural Networks: (Almost) All Local Optima Are Global [paper] [code]
Soheil Feizi, Hamid Javadi, Jesse Zhang, David Tse
NeurIPS, 2018.

Understanding GANs: the LQG Setting [paper]
Soheil Feizi, Changho Suh, Fei Xia, David Tse
Available on arXiv.

Maximally Correlated Principal Component Analysis [paper][code]
Soheil Feizi, David Tse
Available on arXiv.

Spectral Alignment of Graphs [paper] [code]
Soheil Feizi, Gerald Quon, Mariana Mendoza, Muriel Medard, Manolis Kellis, Ali Jadbabaie
IEEE Transactions on Network Science and Engineering, 2019.

Network Infusion to Infer Information Sources in Networks [paper]
Soheil Feizi, Muriel Medard, Gerald Quon, Manolis Kellis, Ken Duffy
IEEE Transactions on Network Science and Engineering, 2018.

Tensor Biclustering [paper] [code]
Soheil Feizi, Hamid Javadi, David Tse
NeurIPS, 2017.

Network Maximal Correlation [paper]
Soheil Feizi*, Ali Makhdoumi* , Ken Duffy, Manolis Kellis, Muriel Medard
IEEE Transactions on Network Science and Engineering, 2017.

Biclustering Using Message Passing [paper] [code]
Luke O'Connor* and Soheil Feizi*
Advances in Neural Information Processing Systems Foundation (NeurIPS), 2014.

Network Deconvolution as a General Method to Distinguish Direct Dependencies in Networks [paper] [code]
Soheil Feizi, Daniel Marbach , Muriel Medard, Manolis Kellis
Nature Biotechnology 31, pp. 726-733, 2013.

Signal Processing/Information Theory

On Network Functional Compression [paper]
Soheil Feizi, Muriel Medard
IEEE Transactions on Information Theory, Vol. 60, No. 9, 2014.

Backward Adaptation for Power Efficient Sampling [paper]
Soheil Feizi, Georgios Angelopoulos, Vivek K Goyal, Muriel Medard
IEEE Transactions on Signal Processing, Vol. 62, No. 16, 2014.

Time-Stampless Adaptive Nonuniform Sampling for Stochastic Signals [paper]
Soheil Feizi, Vivek K Goyal, Muriel Medard
IEEE Transactions on Signal Processing, Vol. 60, No. 10, 2012.

A Power Efficient Sensing/Communication Scheme: Joint Source-Channel-Network Coding by Using Compressive Sensing [paper]
Soheil Feizi, Muriel Medard
Allerton Conference on Communication, Control, and Computing, 2011.

Compressive Sensing Over Networks [paper]
Soheil Feizi, Muriel Medard, Michelle Effros
Allerton Conference on Communication, Control, and Computing, 2010.

Impulsive Noise Cancellation Based on Soft Decision and Recursion [paper]
Sina Zahedpour, Soheil Feizi, Arash Amini, Farrokh Marvasti
IEEE Transactions on Instrumentation and Measurement, Vol. 58, No. 8, 2780-2790, 2009.

Robust Audio Data Hiding Using Correlated Quantization With Histogram-Based Detector [paper]
Ali Akhaee, Mohammad Saberian, Soheil Feizi, Farrokh Marvasti
IEEE Transactions on Multimedia, Vol. 51, No. 6, 2009.