Search Results for author: Ankit Patel

Found 14 papers, 5 papers with code

Transforming Gait: Video-Based Spatiotemporal Gait Analysis

no code implementations17 Mar 2022 R. James Cotton, Emoonah McClerklin, Anthony Cimorelli, Ankit Patel, Tasos Karakostas

Human pose estimation from monocular video is a rapidly advancing field that offers great promise to human movement science and rehabilitation.

Pose Estimation

Spatiotemporal Characterization of Gait from Monocular Videos with Transformers

no code implementations29 Sep 2021 R. James Cotton, Emoonah McClerklin, Anthony Cimorelli, Ankit Patel

Using more than 9000 monocular video from an instrumented gait analysis lab, we evaluated the performance of existing algorithms for measuring kinematics.

Pose Estimation

Shallow Univariate ReLu Networks as Splines: Initialization, Loss Surface, Hessian, & Gradient Flow Dynamics

no code implementations4 Aug 2020 Justin Sahs, Ryan Pyle, Aneel Damaraju, Josue Ortega Caro, Onur Tavaslioglu, Andy Lu, Ankit Patel

Our implicit regularization results are complementary to recent work arXiv:1906. 07842, done independently, which showed that initialization scale critically controls implicit regularization via a kernel-based argument.

Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples

no code implementations19 Jun 2020 Josue Ortega Caro, Yilong Ju, Ryan Pyle, Sourav Dey, Wieland Brendel, Fabio Anselmi, Ankit Patel

Inspired by theoretical work on linear full-width convolutional models, we hypothesize that the local (i. e. bounded-width) convolutional operations commonly used in current neural networks are implicitly biased to learn high frequency features, and that this is one of the root causes of high frequency adversarial examples.

Adversarial Robustness

LEARNING DIFFICULT PERCEPTUAL TASKS WITH HODGKIN-HUXLEY NETWORKS

no code implementations25 Sep 2019 Alan Lockett, Ankit Patel, Paul Pfaffinger

We also demonstrate for the first time that a network with excitatory and inhibitory neurons and nonnegative synapse strengths can successfully solve computer vision problems.

A Functional Characterization of Randomly Initialized Gradient Descent in Deep ReLU Networks

no code implementations25 Sep 2019 Justin Sahs, Aneel Damaraju, Ryan Pyle, Onur Tavaslioglu, Josue Ortega Caro, Hao Yang Lu, Ankit Patel

Despite their popularity and successes, deep neural networks are poorly understood theoretically and treated as 'black box' systems.

Deep Learning-Enhanced Variational Monte Carlo Method for Quantum Many-Body Physics

1 code implementation26 May 2019 Li Yang, Zhaoqi Leng, Guangyuan Yu, Ankit Patel, Wen-Jun Hu, Han Pu

Artificial neural networks have been successfully incorporated into variational Monte Carlo method (VMC) to study quantum many-body systems.

Strongly Correlated Electrons Disordered Systems and Neural Networks

A Bayesian Perspective of Convolutional Neural Networks through a Deconvolutional Generative Model

no code implementations1 Nov 2018 Tan Nguyen, Nhat Ho, Ankit Patel, Anima Anandkumar, Michael. I. Jordan, Richard G. Baraniuk

This conjugate prior yields a new regularizer based on paths rendered in the generative model for training CNNs-the Rendering Path Normalization (RPN).

Towards a Better Understanding and Regularization of GAN Training Dynamics

1 code implementation24 Jun 2018 Weili Nie, Ankit Patel

Generative adversarial networks (GANs) are notoriously difficult to train and the reasons underlying their (non-)convergence behaviors are still not completely understood.

A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations

1 code implementation ICML 2018 Weili Nie, Yang Zhang, Ankit Patel

Backpropagation-based visualizations have been proposed to interpret convolutional neural networks (CNNs), however a theory is missing to justify their behaviors: Guided backpropagation (GBP) and deconvolutional network (DeconvNet) generate more human-interpretable but less class-sensitive visualizations than saliency map.

Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning

no code implementations16 May 2018 Wanjia Liu, Huaijin Chen, Rishab Goel, Yuzhong Huang, Ashok Veeraraghavan, Ankit Patel

Good temporal representations are crucial for video understanding, and the state-of-the-art video recognition framework is based on two-stream networks.

Action Recognition Atari Games +6

Training Neural Networks Without Gradients: A Scalable ADMM Approach

2 code implementations6 May 2016 Gavin Taylor, Ryan Burmeister, Zheng Xu, Bharat Singh, Ankit Patel, Tom Goldstein

With the growing importance of large network models and enormous training datasets, GPUs have become increasingly necessary to train neural networks.

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