Coreset-Based Adaptive Tracking. - Abhimanyu Dubey; Nikhil Naik 003; Dan Raviv; Rahul Sukthankar; Ramesh Raskar (CoRR, 2015)

Deep Learning the City: Quantifying Urban Perception at a Global Scale. - Abhimanyu Dubey; Nikhil Naik 003; Devi Parikh; Ramesh Raskar; César A. Hidalgo 001 (ECCV (1), 2016)

Examining Representational Similarity in ConvNets and the Primate Visual Cortex. - Abhimanyu Dubey; Jayadeva; Sumeet Agarwal (CoRR, 2016)

Modeling Image Virality with Pairwise Spatial Transformer Networks. - Abhimanyu Dubey; Sumeet Agarwal (ACM Multimedia, 2017)

Training with Confusion for Fine-Grained Visual Classification. - Abhimanyu Dubey; Otkrist Gupta; Pei Guo; Ramesh Raskar; Ryan Farrell; Nikhil Naik 003 (CoRR, 2017)

Learning Neural Network Classifiers with Low Model Complexity. - Jayadeva; Himanshu Pant; Mayank Sharma; Abhimanyu Dubey; Sumit Soman; Sai Guruju; Nihal Goalla (CoRR, 2017)

Coreset-Based Neural Network Compression. - Abhimanyu Dubey; Moitreya Chatterjee; Narendra Ahuja (ECCV (7), 2018)

Pairwise Confusion for Fine-Grained Visual Classification. - Abhimanyu Dubey; Otkrist Gupta; Pei Guo; Ramesh Raskar; Ryan Farrell; Nikhil Naik 003 (ECCV (12), 2018)

TuringBox: An Experimental Platform for the Evaluation of AI Systems. - Ziv Epstein; Blakeley H. Payne; Judy Hanwen Shen; Casey Jisoo Hong; Bjarke Felbo; Abhimanyu Dubey; Matthew Groh; Nick Obradovich; Manuel Cebrián; Iyad Rahwan (IJCAI, 2018)

Maximum-Entropy Fine Grained Classification. - Abhimanyu Dubey; Otkrist Gupta; Ramesh Raskar; Nikhil Naik 003 (NeurIPS, 2018)

MemeSequencer: Sparse Matching for Embedding Image Macros. - Abhimanyu Dubey; Esteban Moro; Manuel Cebrián; Iyad Rahwan (WWW, 2018)

Closing the AI Knowledge Gap. - Ziv Epstein; Blakeley H. Payne; Judy Hanwen Shen; Abhimanyu Dubey; Bjarke Felbo; Matthew Groh; Nick Obradovich; Manuel Cebrián; Iyad Rahwan (CoRR, 2018)

No Peek: A Survey of private distributed deep learning. - Praneeth Vepakomma; Tristan Swedish; Ramesh Raskar; Otkrist Gupta; Abhimanyu Dubey (CoRR, 2018)

Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions. - Shayne O'Brien; Matthew Groh; Abhimanyu Dubey (CoRR, 2018)

Defense Against Adversarial Images Using Web-Scale Nearest-Neighbor Search. - Abhimanyu Dubey; Laurens van der Maaten; Zeki Yalniz; Yixuan Li 001; Dhruv Mahajan 001 (CVPR, 2019)

Thompson Sampling on Symmetric Alpha-Stable Bandits. - Abhimanyu Dubey; Alex Pentland (IJCAI, 2019)

Communication Topologies Between Learning Agents in Deep Reinforcement Learning. - Dhaval Adjodah; Dan Calacci; Abhimanyu Dubey; Anirudh Goyal; Peter M. Krafft; Esteban Moro; Alex Pentland (CoRR, 2019)

Thompson Sampling on Symmetric α-Stable Bandits. - Abhimanyu Dubey; Alex Pentland (CoRR, 2019)

Smaller Models, Better Generalization. - Mayank Sharma; Suraj Tripathi; Abhimanyu Dubey; Jayadeva; Sai Guruju; Nihal Goalla (CoRR, 2019)

Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning. - Dhaval Adjodah; Dan Calacci; Abhimanyu Dubey; Anirudh Goyal; P. M. Krafft; Esteban Moro; Alex Pentland (AAMAS, 2020)

Private and Byzantine-Proof Cooperative Decision-Making. - Abhimanyu Dubey; Alex Pentland (AAMAS, 2020)

Cooperative Multi-Agent Bandits with Heavy Tails. - Abhimanyu Dubey; Alex 'Sandy' Pentland (ICML, 2020)

Kernel Methods for Cooperative Multi-Agent Contextual Bandits. - Abhimanyu Dubey; Alex 'Sandy' Pentland (ICML, 2020)

Differentially-Private Federated Linear Bandits. - Abhimanyu Dubey; Alex 'Sandy' Pentland (NeurIPS, 2020)

No-Regret Algorithms for Private Gaussian Process Bandit Optimization. - Abhimanyu Dubey (AISTATS, 2021)

Adaptive Methods for Real-World Domain Generalization. - Abhimanyu Dubey; Vignesh Ramanathan; Alex Pentland; Dhruv Mahajan 001 (CVPR, 2021)

One More Step Towards Reality: Cooperative Bandits with Imperfect Communication. - Udari Madhushani; Abhimanyu Dubey; Naomi Ehrich Leonard; Alex Pentland (NeurIPS, 2021)

Provably Efficient Cooperative Multi-Agent Reinforcement Learning with Function Approximation. - Abhimanyu Dubey; Alex Pentland (CoRR, 2021)

Adaptive Methods for Aggregated Domain Generalization. - Xavier Thomas; Dhruv Mahajan 001; Alex Pentland; Abhimanyu Dubey (CoRR, 2021)

Social Influence Leads to the Formation of Diverse Local Trends. - Ziv Epstein; Matthew Groh; Abhimanyu Dubey; Alex Pentland (Proc. ACM Hum. Comput. Interact., 2021)

Scalable Interpretability via Polynomials. - Abhimanyu Dubey; Filip Radenovic; Dhruv Mahajan 001 (NeurIPS, 2022)

Neural Basis Models for Interpretability. - Filip Radenovic; Abhimanyu Dubey; Dhruv Mahajan 001 (NeurIPS, 2022)

Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training. - Filip Radenovic; Abhimanyu Dubey; Abhishek Kadian; Todor Mihaylov; Simon Vandenhende; Yash Patel; Yi Wen 006; Vignesh Ramanathan; Dhruv Mahajan 001 (CVPR, 2023)

PACO: Parts and Attributes of Common Objects. - Vignesh Ramanathan; Anmol Kalia; Vladan Petrovic; Yi Wen 006; Baixue Zheng; Baishan Guo; Rui Wang 067; Aaron Marquez; Rama Kovvuri; Abhishek Kadian; Amir Mousavi; Yiwen Song; et al. (CVPR, 2023)

Cola: A Benchmark for Compositional Text-to-image Retrieval. - Arijit Ray; Filip Radenovic; Abhimanyu Dubey; Bryan A. Plummer; Ranjay Krishna; Kate Saenko (NeurIPS, 2023)

COLA: How to adapt vision-language models to Compose Objects Localized with Attributes? - Arijit Ray; Filip Radenovic; Abhimanyu Dubey; Bryan A. Plummer; Ranjay Krishna; Kate Saenko (CoRR, 2023)

Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack. - Xiaoliang Dai; Ji Hou; Chih-Yao Ma; Sam S. Tsai; Jialiang Wang 001; Rui Wang 067; Peizhao Zhang; Simon Vandenhende; Xiaofang Wang; Abhimanyu Dubey; Matthew Yu; Abhishek Kadian; et al. (CoRR, 2023)

Context Diffusion: In-Context Aware Image Generation. - Ivona Najdenkoska; Animesh Sinha; Abhimanyu Dubey; Dhruv Mahajan 001; Vignesh Ramanathan; Filip Radenovic (ECCV (77), 2024)

The Llama 3 Herd of Models. - Abhimanyu Dubey; Abhinav Jauhri; Abhinav Pandey; Abhishek Kadian; Ahmad Al-Dahle; Aiesha Letman; Akhil Mathur; Alan Schelten; Amy Yang; Angela Fan; Anirudh Goyal; Anthony Hartshorn; et al. (CoRR, 2024)