Search Results for author: Ayush Chopra

Found 21 papers, 3 papers with code

SARC: Soft Actor Retrospective Critic

1 code implementation28 Jun 2023 Sukriti Verma, Ayush Chopra, Jayakumar Subramanian, Mausoom Sarkar, Nikaash Puri, Piyush Gupta, Balaji Krishnamurthy

The two-time scale nature of SAC, which is an actor-critic algorithm, is characterised by the fact that the critic estimate has not converged for the actor at any given time, but since the critic learns faster than the actor, it ensures eventual consistency between the two.

Bayesian calibration of differentiable agent-based models

no code implementations24 May 2023 Arnau Quera-Bofarull, Ayush Chopra, Anisoara Calinescu, Michael Wooldridge, Joel Dyer

Agent-based modelling (ABMing) is a powerful and intuitive approach to modelling complex systems; however, the intractability of ABMs' likelihood functions and the non-differentiability of the mathematical operations comprising these models present a challenge to their use in the real world.

Bayesian Inference Variational Inference

Differentiable Agent-based Epidemiology

1 code implementation20 Jul 2022 Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Arnau Quera-Bofarull, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar

Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of complex, dynamic infections under varying conditions and navigate uncertain environments.

Epidemiology Navigate

On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models

no code implementations8 May 2022 Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian

Conditional image generation has paved the way for several breakthroughs in image editing, generating stock photos and 3-D object generation.

Conditional Image Generation

Learning to Censor by Noisy Sampling

no code implementations23 Mar 2022 Ayush Chopra, Abhinav Java, Abhishek Singh, Vivek Sharma, Ramesh Raskar

The goal of this work is to protect sensitive information when learning from point clouds; by censoring the sensitive information before the point cloud is released for downstream tasks.

Attribute

Decouple-and-Sample: Protecting sensitive information in task agnostic data release

no code implementations17 Mar 2022 Abhishek Singh, Ethan Garza, Ayush Chopra, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar

While releasing datasets continues to make a big impact in various applications of computer vision, its impact is mostly realized when data sharing is not inhibited by privacy concerns.

AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning

no code implementations2 Dec 2021 Ayush Chopra, Surya Kant Sahu, Abhishek Singh, Abhinav Java, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar

In this work, we introduce AdaSplit which enables efficiently scaling SL to low resource scenarios by reducing bandwidth consumption and improving performance across heterogeneous clients.

Federated Learning

DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks

no code implementations9 Oct 2021 Ayush Chopra, Esma Gel, Jayakumar Subramanian, Balaji Krishnamurthy, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley, Ramesh Raskar

We introduce DeepABM, a framework for agent-based modeling that leverages geometric message passing of graph neural networks for simulating action and interactions over large agent populations.

Sanitizer: Sanitizing data for anonymizing sensitive information

no code implementations29 Sep 2021 Abhishek Singh, Ethan Garza, Ayush Chopra, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar

This is done in a two-step process: first, we develop a method that encodes unstructured image-like modality into a structured representation bifurcated by sensitive and non-sensitive representation.

Attribute

ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priors

no code implementations ICCV 2021 Ayush Chopra, Rishabh Jain, Mayur Hemani, Balaji Krishnamurthy

Image-based virtual try-on involves synthesizing perceptually convincing images of a model wearing a particular garment and has garnered significant research interest due to its immense practical applicability.

SSIM Virtual Try-on

COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms

no code implementations21 Dec 2020 Rohan Sukumaran, Parth Patwa, T V Sethuraman, Sheshank Shankar, Rishank Kanaparti, Joseph Bae, Yash Mathur, Abhishek Singh, Ayush Chopra, Myungsun Kang, Priya Ramaswamy, Ramesh Raskar

In this study, we understand trends in the spread of COVID-19 by utilizing the results of self-reported COVID-19 symptoms surveys as an alternative to COVID-19 testing reports.

Time Series Forecasting

MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance

no code implementations3 Sep 2020 Anubha Kabra, Ayush Chopra, Nikaash Puri, Pinkesh Badjatiya, Sukriti Verma, Piyush Gupta, Balaji K

Training a classification model on a dataset where the instances of one class outnumber those of the other class is a challenging problem.

Data Augmentation Fraud Detection +1

Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks

no code implementations24 Jun 2020 Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian

Deep neural networks (DNNs) are powerful learning machines that have enabled breakthroughs in several domains.

SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation

no code implementations30 Apr 2020 Siddhartha Gairola, Mayur Hemani, Ayush Chopra, Balaji Krishnamurthy

Few-shot segmentation (FSS) methods perform image segmentation for a particular object class in a target (query) image, using a small set of (support) image-mask pairs.

Image Segmentation Segmentation +1

SieveNet: A Unified Framework for Robust Image-Based Virtual Try-On

1 code implementation17 Jan 2020 Surgan Jandial, Ayush Chopra, Kumar Ayush, Mayur Hemani, Abhijeet Kumar, Balaji Krishnamurthy

An efficient framework for this is composed of two stages: (1) warping (transforming) the try-on cloth to align with the pose and shape of the target model, and (2) a texture transfer module to seamlessly integrate the warped try-on cloth onto the target model image.

Geometric Matching Virtual Try-on

Hierarchy Influenced Differential Evolution: A Motor Operation Inspired Approach

no code implementations17 Feb 2017 Shubham Dokania, Ayush Chopra, Feroz Ahmad, Anil Singh Parihar

In the present work, we introduce an algorithm for mathematical optimisation that derives its intuition from the hierarchical and distributed operations of the human motor system.

Decision Making

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