Ankit B. Patel

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 38

Top Topics

Finite Automata

Formal Languages

Top Venues

Frontiers Artif. Intell.

Publications

Hao Liang, Josue Ortega Caro, Vikram Maheshri, Ankit B. Patel, Guha Balakrishnan
Linking convolutional kernel size to generalization bias in face analysis CNNs. WACV (2024)
Satpreet Harcharan Singh, Kevin Jiang, Kanchan Bhasin, Ashutosh Sabharwal, Nidal Moukaddam, Ankit B. Patel
RACER: An LLM-powered Methodology for Scalable Analysis of Semi-structured Mental Health Interviews. CoRR (2024)
Zhe Li, Josue Ortega Caro, Evgenia Rusak, Wieland Brendel, Matthias Bethge, Fabio Anselmi, Ankit B. Patel, Andreas S. Tolias, Xaq Pitkow
Robust deep learning object recognition models rely on low frequency information in natural images. PLoS Comput. Biol. 19 (3) (2023)
McKell Woodland, Nihil Patel, Mais Al Taie, Joshua P. Yung, Tucker J. Netherton, Ankit B. Patel, Kristy K. Brock
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image Segmentation. UNSURE@MICCAI (2023)
Hao Liang, Josue Ortega Caro, Vikram Maheshri, Ankit B. Patel, Guha Balakrishnan
Towards causally linking architectural parametrizations to algorithmic bias in neural networks. CoRR (2023)
McKell Woodland, Mais Al Taie, Jessica Albuquerque Marques Silva, Mohamed Eltaher, Frank Mohn, Alexander Shieh, Austin Castelo, Suprateek Kundu, Joshua P. Yung, Ankit B. Patel, Kristy K. Brock
Importance of Feature Extraction in the Calculation of Fréchet Distance for Medical Imaging. CoRR (2023)
McKell Woodland, Nihil Patel, Mais Al Taie, Joshua P. Yung, Tucker J. Netherton, Ankit B. Patel, Kristy K. Brock
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image Segmentation. CoRR (2023)
McKell Woodland, John Wood, Caleb O'Connor, Ankit B. Patel, Kristy K. Brock
StyleGAN2-based Out-of-Distribution Detection for Medical Imaging. CoRR (2023)
Ryan Pyle, Sebastian Musslick, Jonathan D. Cohen, Ankit B. Patel
A Quantitative Approach to Predicting Representational Learning and Performance in Neural Networks. CoRR (2023)
Bishal Lamichhane, Nidal Moukaddam, Ankit B. Patel, Ashutosh Sabharwal
Dyadic Interaction Assessment from Free-living Audio for Depression Severity Assessment. CoRR (2022)
Bishal Lamichhane, Nidal Moukaddam, Ankit B. Patel, Ashutosh Sabharwal
Dyadic Interaction Assessment from Free-living Audio for Depression Severity Assessment. INTERSPEECH (2022)
McKell Woodland, John Wood, Brian M. Anderson, Suprateek Kundu, Ethan Lin, Eugene J. Koay, Bruno Odisio, Caroline Chung, Hyunseon Christine Kang, Aradhana M. Venkatesan, Sireesha Yedururi, Brian De, Yuan-Mao Lin, Ankit B. Patel, Kristy K. Brock
Evaluating the Performance of StyleGAN2-ADA on Medical Images. SASHIMI@MICCAI (2022)
Nikos Karantzas, Emma Besier, Josue Ortega Caro, Xaq Pitkow, Andreas S. Tolias, Ankit B. Patel, Fabio Anselmi
Understanding robustness and generalization of artificial neural networks through Fourier masks. CoRR (2022)
Varun Suriyanarayana, Onur Tavaslioglu, Ankit B. Patel, Andrew J. Schaefer
Reinforcement learning of simplex pivot rules: a proof of concept. Optim. Lett. 16 (8) (2022)
McKell Woodland, John Wood, Brian M. Anderson, Suprateek Kundu, Ethan Lin, Eugene J. Koay, Bruno Odisio, Caroline Chung, Hyunseon Christine Kang, Aradhana M. Venkatesan, Sireesha Yedururi, Brian De, Yuan-Mao Lin, Ankit B. Patel, Kristy K. Brock
Evaluating the Performance of StyleGAN2-ADA on Medical Images. CoRR (2022)
Nikos Karantzas, Emma Besier, Josue Ortega Caro, Xaq Pitkow, Andreas S. Tolias, Ankit B. Patel, Fabio Anselmi
Understanding Robustness and Generalization of Artificial Neural Networks Through Fourier Masks. Frontiers Artif. Intell. 5 (2022)
Fabio Anselmi, Ankit B. Patel
Editorial: Symmetry as a guiding principle in artificial and brain neural networks. Frontiers Comput. Neurosci. 16 (2022)
Justin Sahs, Ryan Pyle, Aneel Damaraju, Josue Ortega Caro, Onur Tavaslioglu, Andy Lu, Fabio Anselmi, Ankit B. Patel
Shallow Univariate ReLU Networks as Splines: Initialization, Loss Surface, Hessian, and Gradient Flow Dynamics. Frontiers Artif. Intell. 5 (2022)
Bishal Lamichhane, Nidal Moukaddam, Ankit B. Patel, Ashutosh Sabharwal
ECoNet: Estimating Everyday Conversational Network From Free-Living Audio for Mental Health Applications. IEEE Pervasive Comput. 21 (2) (2022)
Micah Goldblum, Avi Schwarzschild, Ankit B. Patel, Tom Goldstein
Adversarial attacks on machine learning systems for high-frequency trading. ICAIF (2021)
Sonu Subudhi, Ashish Verma, Ankit B. Patel, C. Corey Hardin, Melin J. Khandekar, Hang Lee, Dustin McEvoy, Triantafyllos Stylianopoulos, Lance L. Munn, Sayon Dutta, Rakesh K. Jain
Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19. npj Digit. Medicine 4 (2021)
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Animashree Anandkumar
Semi-Supervised StyleGAN for Disentanglement Learning. ICML (2020)
Weili Nie, Zichao Wang, Ankit B. Patel, Richard G. Baraniuk
An Improved Semi-Supervised VAE for Learning Disentangled Representations. CoRR (2020)
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Anima Anandkumar
Semi-Supervised StyleGAN for Disentanglement Learning. CoRR (2020)
Micah Goldblum, Avi Schwarzschild, Naftali Cohen, Tucker Balch, Ankit B. Patel, Tom Goldstein
Adversarial Attacks on Machine Learning Systems for High-Frequency Trading. CoRR (2020)
Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Animashree Anandkumar
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning. CoRR (2020)
Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Anima Anandkumar
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning. NeurIPS (2020)
Huaijin G. Chen, Wanjia Liu, Rishab Goel, Rhonald C. Lua, Siddharth Mittal, Yuzhong Huang, Ashok Veeraraghavan, Ankit B. Patel
Fast Retinomorphic Event-Driven Representations for Video Gameplay and Action Recognition. IEEE Trans. Computational Imaging 6 (2020)
Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks. ICLR (Poster) (2019)
Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks. CoRR (2019)
Nhat Ho, Tan M. Nguyen, Ankit B. Patel, Anima Anandkumar, Michael I. Jordan, Richard G. Baraniuk
Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning. CoRR (2018)
Wanjia Liu, Huaijin G. Chen, Rishab Goel, Yuzhong Huang, Ashok Veeraraghavan, Ankit B. Patel
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning. CoRR (2018)
Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Ankit B. Patel
Overcomplete Frame Thresholding for Acoustic Scene Analysis. CoRR (2017)
Gavin Taylor, Ryan Burmeister, Zheng Xu, Bharat Singh, Ankit B. Patel, Tom Goldstein
Training Neural Networks Without Gradients: A Scalable ADMM Approach. CoRR (2016)
Minh Tan Nguyen, Wanjia Liu, Ethan Perez, Richard G. Baraniuk, Ankit B. Patel
Semi-Supervised Learning with the Deep Rendering Mixture Model. CoRR (2016)
Gavin Taylor, Ryan Burmeister, Zheng Xu, Bharat Singh, Ankit B. Patel, Tom Goldstein
Training Neural Networks Without Gradients: A Scalable ADMM Approach. ICML (2016)
Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk
A Probabilistic Framework for Deep Learning. CoRR (2016)
Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk
A Probabilistic Framework for Deep Learning. NIPS (2016)
Ali Mousavi, Ankit B. Patel, Richard G. Baraniuk
A deep learning approach to structured signal recovery. Allerton (2015)
Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk
A Probabilistic Theory of Deep Learning. CoRR (2015)
Ali Mousavi, Ankit B. Patel, Richard G. Baraniuk
A Deep Learning Approach to Structured Signal Recovery. CoRR (2015)