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Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning


Oct 02, 2020
Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Animashree Anandkumar

* 21 pages, NeurIPS 2020 

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An Improved Semi-Supervised VAE for Learning Disentangled Representations


Jun 22, 2020
Weili Nie, Zichao Wang, Ankit B. Patel, Richard G. Baraniuk


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LaRVAE: Label Replacement VAE for Semi-Supervised Disentanglement Learning


Jun 12, 2020
Weili Nie, Zichao Wang, Ankit B. Patel, Richard G. Baraniuk


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Semi-Supervised StyleGAN for Disentanglement Learning


Mar 06, 2020
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debhath, Anjul Patney, Ankit B. Patel, Anima Anandkumar

* 20 pages, 4 tables, 18 figures 

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Adversarial Attacks on Machine Learning Systems for High-Frequency Trading


Mar 04, 2020
Micah Goldblum, Avi Schwarzschild, Ankit B. Patel, Tom Goldstein


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Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks


Feb 27, 2019
Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel

* 15 Pages, 13 Figures, Accepted to ICLR 2019 

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Semi-Supervised Learning with the Deep Rendering Mixture Model


Dec 06, 2016
Tan Nguyen, Wanjia Liu, Ethan Perez, Richard G. Baraniuk, Ankit B. Patel


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A Probabilistic Framework for Deep Learning


Dec 06, 2016
Ankit B. Patel, Tan Nguyen, Richard G. Baraniuk

* arXiv admin note: substantial text overlap with arXiv:1504.00641 

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A Deep Learning Approach to Structured Signal Recovery


Aug 17, 2015
Ali Mousavi, Ankit B. Patel, Richard G. Baraniuk

* In Proceeding of 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton) 

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A Probabilistic Theory of Deep Learning


Apr 02, 2015
Ankit B. Patel, Tan Nguyen, Richard G. Baraniuk

* 56 pages, 6 figures, 2 tables 

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