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ORCIDAyush Chopra
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2020 – today
- 2024
[c25]Ayush Chopra, Arnau Quera-Bofarull, Nurullah Giray Kuru, Michael J. Wooldridge, Ramesh Raskar:
Private Agent-Based Modeling. AAMAS 2024: 381-390- [c24]Ayush Chopra, Jayakumar Subramanian, Balaji Krishnamurthy, Ramesh Raskar:
flame: A Framework for Learning in Agent-based ModEls. AAMAS 2024: 391-399 - [c23]Gauri Gupta, Ritvik Kapila, Ayush Chopra, Ramesh Raskar:
First 100 days of Pandemic: An Interplay of Pharmaceutical, Behavioral and Digital Interventions - A Study using Agent Based Modeling. AAMAS 2024: 761-770 - [i21]Gauri Gupta, Ritvik Kapila, Ayush Chopra, Ramesh Raskar:
First 100 days of pandemic; an interplay of pharmaceutical, behavioral and digital interventions - A study using agent based modeling. CoRR abs/2401.04795 (2024) - [i20]Ayush Chopra, Arnau Quera-Bofarull, Nurullah Giray Kuru, Michael J. Wooldridge, Ramesh Raskar:
Private Agent-Based Modeling. CoRR abs/2404.12983 (2024) - [i19]Ayush Chopra, Shashank Kumar, Nurullah Giray Kuru, Ramesh Raskar, Arnau Quera-Bofarull:
On the limits of agency in agent-based models. CoRR abs/2409.10568 (2024) - 2023
- [c22]Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Arnau Quera-Bofarull, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar:
Differentiable Agent-based Epidemiology. AAMAS 2023: 1848-1857 - [c21]Arnau Quera-Bofarull, Ayush Chopra, Joseph Aylett-Bullock, Carolina Cuesta-Lázaro, Anisoara Calinescu, Ramesh Raskar, Michael J. Wooldridge:
Don't Simulate Twice: One-Shot Sensitivity Analyses via Automatic Differentiation. AAMAS 2023: 1867-1876 - [c20]Joel Dyer
, Arnau Quera-Bofarull, Ayush Chopra, J. Doyne Farmer, Anisoara Calinescu, Michael J. Wooldridge:
Gradient-Assisted Calibration for Financial Agent-Based Models. ICAIF 2023: 288-296 - [i18]Arnau Quera-Bofarull, Ayush Chopra, Anisoara Calinescu, Michael J. Wooldridge, Joel Dyer:
Bayesian calibration of differentiable agent-based models. CoRR abs/2305.15340 (2023) - [i17]Sukriti Verma, Ayush Chopra, Jayakumar Subramanian, Mausoom Sarkar, Nikaash Puri, Piyush Gupta, Balaji Krishnamurthy:
SARC: Soft Actor Retrospective Critic. CoRR abs/2306.16503 (2023) - 2022
- [c19]Ayush Chopra, Abhinav Java, Abhishek Singh, Vivek Sharma, Ramesh Raskar:
Learning to Censor by Noisy Sampling. ECCV (13) 2022: 378-395 - [c18]Abhishek Singh, Ethan Garza, Ayush Chopra, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
Decouple-and-Sample: Protecting Sensitive Information in Task Agnostic Data Release. ECCV (13) 2022: 499-517 - [c17]Surgan Jandial, Pinkesh Badjatiya, Pranit Chawla, Ayush Chopra, Mausoom Sarkar, Balaji Krishnamurthy:
SAC: Semantic Attention Composition for Text-Conditioned Image Retrieval. WACV 2022: 597-606 - [i16]Ayush Chopra, Abhinav Java, Abhishek Singh, Vivek Sharma, Ramesh Raskar:
Learning to Censor by Noisy Sampling. CoRR abs/2203.12192 (2022) - [i15]Abhishek Singh, Ethan Garza, Ayush Chopra, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
Decouple-and-Sample: Protecting sensitive information in task agnostic data release. CoRR abs/2203.13204 (2022) - [i14]Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models. CoRR abs/2205.03859 (2022) - [i13]Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar:
Differentiable Agent-based Epidemiology. CoRR abs/2207.09714 (2022) - 2021
- [c16]Pranit Chawla, Surgan Jandial, Pinkesh Badjatiya, Ayush Chopra, Mausoom Sarkar, Balaji Krishnamurthy:
Leveraging Style and Content Features for Text Conditioned Image Retrieval. CVPR Workshops 2021: 3978-3982 - [c15]Abhishek Singh, Ayush Chopra, Ethan Garza, Emily Zhang, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for Deep Neural Networks. CVPR 2021: 12125-12135 - [c14]Nataraj Kuntagod, Sanjay Podder, Rambhau Eknath Rote, Satya Sai Srinivas Abbabathula, Neelkanth Mishra, Ayush Chopra:
Ecosystem approach to sustainable aquaculture for smallholder farmers. GHTC 2021: 138-141 - [c13]Ayush Chopra, Rishabh Jain, Mayur Hemani, Balaji Krishnamurthy:
ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priors. ICCV 2021: 5413-5422 - [c12]Ayush Chopra, Ramesh Raskar, Jayakumar Subramanian, Balaji Krishnamurthy, Esma Senturk Gel, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley:
DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks - a Case Study For Covid-19 Spread and Interventions. WSC 2021: 1-12 - [i12]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:
COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms. CoRR abs/2101.10266 (2021) - [i11]Ayush Chopra, Rishabh Jain, Mayur Hemani, Balaji Krishnamurthy:
ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priors. CoRR abs/2109.07001 (2021) - [i10]Ayush Chopra, Esma Senturk Gel, Jayakumar Subramanian, Balaji Krishnamurthy, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley, Ramesh Raskar:
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks. CoRR abs/2110.04421 (2021) - [i9]Ayush Chopra, Surya Kant Sahu, Abhishek Singh, Abhinav Java, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning. CoRR abs/2112.01637 (2021) - 2020
- [c11]Anubha Kabra, Ayush Chopra, Nikaash Puri, Pinkesh Badjatiya, Sukriti Verma, Piyush Gupta, Balaji Krishnamurthy:
MixBoost: Synthetic Oversampling using Boosted Mixup for Handling Extreme Imbalance. ICDM 2020: 1082-1087 - [c10]Siddhartha Gairola, Mayur Hemani, Ayush Chopra, Balaji Krishnamurthy:
SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation. IJCAI 2020: 573-579 - [c9]Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian:
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks. KDD 2020: 1123-1131 - [c8]Surgan Jandial, Ayush Chopra, Kumar Ayush, Mayur Hemani, Abhijeet Kumar, Balaji Krishnamurthy:
SieveNet: A Unified Framework for Robust Image-Based Virtual Try-On. WACV 2020: 2171-2179 - [c7]Anirudh Singhal, Ayush Chopra, Kumar Ayush, Utkarsh Patel, Balaji Krishnamurthy:
Towards a Unified Framework for Visual Compatibility Prediction. WACV 2020: 3596-3605 - [i8]Surgan Jandial, Ayush Chopra, Kumar Ayush, Mayur Hemani, Abhijeet Kumar, Balaji Krishnamurthy:
SieveNet: A Unified Framework for Robust Image-Based Virtual Try-On. CoRR abs/2001.06265 (2020) - [i7]Siddhartha Gairola, Mayur Hemani, Ayush Chopra, Balaji Krishnamurthy:
SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation. CoRR abs/2004.15014 (2020) - [i6]Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian:
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks. CoRR abs/2006.13593 (2020) - [i5]Surgan Jandial, Ayush Chopra, Pinkesh Badjatiya, Pranit Chawla, Mausoom Sarkar, Balaji Krishnamurthy:
TRACE: Transform Aggregate and Compose Visiolinguistic Representations for Image Search with Text Feedback. CoRR abs/2009.01485 (2020) - [i4]Anubha Kabra, Ayush Chopra, Nikaash Puri, Pinkesh Badjatiya, Sukriti Verma, Piyush Gupta, Balaji Krishnamurthy:
MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance. CoRR abs/2009.01571 (2020) - [i3]Sheshank Shankar, Ayush Chopra, Rishank Kanaparti, Myungsun Kang, Abhishek Singh, Ramesh Raskar:
Proximity Sensing for Contact Tracing. CoRR abs/2009.04991 (2020) - [i2]Abhishek Singh, Ayush Chopra, Vivek Sharma, Ethan Garza, Emily Zhang, Praneeth Vepakomma, Ramesh Raskar:
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks. CoRR abs/2012.11025 (2020)
2010 – 2019
- 2019
- [c6]Ayush Chopra, Abhishek Sinha, Hiresh Gupta, Mausoom Sarkar, Kumar Ayush, Balaji Krishnamurthy:
Powering Robust Fashion Retrieval With Information Rich Feature Embeddings. CVPR Workshops 2019: 326-334 - [c5]Kumar Ayush, Surgan Jandial, Ayush Chopra, Mayur Hemani, Balaji Krishnamurthy:
Robust Cloth Warping via Multi-Scale Patch Adversarial Loss for Virtual Try-On Framework. ICCV Workshops 2019: 1279-1281 - [c4]Kumar Ayush, Surgan Jandial, Ayush Chopra, Balaji Krishnamurthy:
Powering Virtual Try-On via Auxiliary Human Segmentation Learning. ICCV Workshops 2019: 3193-3196 - 2018
- [c3]Kushagra Mahajan, Tarasha Khurana, Ayush Chopra, Isha Gupta, Chetan Arora, Atul Rai:
Pose Aware Fine-Grained Visual Classification Using Pose Experts. ICIP 2018: 2381-2385 - 2017
- [c2]Shubham Dokania, Ayush Chopra, Feroz Ahmad, Anil Singh Parihar:
Hierarchy Influenced Differential Evolution: A Motor Operation Inspired Approach. IJCCI 2017: 207-214 - [c1]Shubham Dokania, Ayush Chopra, Feroz Ahmad, S. Indu, Santanu Chaudhury:
Unsupervised Feature Descriptors Based Facial Tracking over Distributed Geospatial Subspaces. PReMI 2017: 196-202 - [i1]Shubham Dokania, Ayush Chopra, Feroz Ahmad, Om Prakash Verma:
Hierarchy Influenced Differential Evolution: A Motor Operation Inspired Approach. CoRR abs/1702.05308 (2017)
Coauthor Index
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last updated on 2024-10-15 00:20 CEST by the dblp team
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