Abhinav Moudgil

According to our database, Abhinav Moudgil authored at least 13 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity.

Ningyuan Huang, Miguel Sarabia, Abhinav Moudgil, Pau Rodríguez, Luca Zappella, Federico Danieli

CoRR, June, 2025

PyLO: Towards Accessible Learned Optimizers in PyTorch.

Paul Janson, Benjamin Thérien, Quentin Anthony, Xiaolong Huang, Abhinav Moudgil, Eugene Belilovsky

CoRR, June, 2025

Learning Versatile Optimizers on a Compute Diet.

Abhinav Moudgil, Boris Knyazev, Guillaume Lajoie, Eugene Belilovsky

CoRR, January, 2025

Celo: Training Versatile Learned Optimizers on a Compute Diet.

Abhinav Moudgil, Boris Knyazev, Guillaume Lajoie, Eugene Belilovsky

Trans. Mach. Learn. Res., 2025

Meta-learning Optimizers for Communication-Efficient Learning.

Charles-Étienne Joseph, Benjamin Thérien, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky

Trans. Mach. Learn. Res., 2025

Accelerating Training with Neuron Interaction and Nowcasting Networks.

Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2023

Can We Learn Communication-Efficient Optimizers?

Charles-Étienne Joseph, Benjamin Thérien, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky

CoRR, 2023

2022

Towards Scaling Difference Target Propagation by Learning Backprop Targets.

Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio

Proceedings of the International Conference on Machine Learning, 2022

2021

SOAT: A Scene- and Object-Aware Transformer for Vision-and-Language Navigation.

Abhinav Moudgil, Arjun Majumdar, Harsh Agrawal, Stefan Lee, Dhruv Batra

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Contrast and Classify: Training Robust VQA Models.

Yash Kant, Abhinav Moudgil, Dhruv Batra, Devi Parikh, Harsh Agrawal

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Contrast and Classify: Alternate Training for Robust VQA.

Yash Kant, Abhinav Moudgil, Dhruv Batra, Devi Parikh, Harsh Agrawal

CoRR, 2020

Exploring 3 R's of Long-term Tracking: Re-detection, Recovery and Reliability.

Shyamgopal Karthik, Abhinav Moudgil, Vineet Gandhi

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

2018

Long-Term Visual Object Tracking Benchmark.

Abhinav Moudgil, Vineet Gandhi

Proceedings of the Computer Vision - ACCV 2018, 2018