Research Interests:  Continual Learning   Binarization & Pruning     Uncertainty & Active Learning Unsupervised Learning  Others   


Continual Learning

GDumb: A Simple Approach that Questions Our Progress in Continual Learning
Ameya Prabhu, Philip H.S. Torr, Puneet K. Dokania
In ECCV 2020 (Oral)
[PDF] [Code] [Talk] [Teaser] [Slides] [Slides (V2)]


Uncertainty & Active Learning

Sampling Bias in Deep Active Classification: An Empirical Study
Ameya Prabhu, Charles Dognin, Maneesh Singh
In EMNLP 2019
[PDF] [Code] [Poster]


Unsupervised Learning

Do We Need Supervision in Multi-Object Tracking?
Shyamgopal Karthik, Ameya Prabhu, Vineet Gandhi
(Under review)
[PDF] [Code]


Binarization & Pruning

STQ-Nets: Unifying Network Binarization and Structured Pruning
Aurobindo Munagala, Ameya Prabhu, Anoop Namboodiri
In BMVC 2020
[PDF] [Talk & Slides]

Exploring Binarization and Pruning for Convolutional Neural Networks
Ameya Prabhu
Master’s Thesis, IIIT-H
[PDF] [Slides]

Deep Expander Networks: Efficient Deep Networks from Graph Theory, ECCV 2018 (Oral)
Ameya Prabhu, Girish Varma, Anoop Namboodiri
In ECCV 2018 (Oral)
[PDF] [Code] [Talk] [Slides] [Poster]

Hybrid Binary Networks: Optimizing for Accuracy, Efficiency and Memory
Ameya Prabhu, Vishal Batchu, Rohit Gajawada, Aurobindo Munagala, Anoop Namboodiri
In WACV 2018 (Oral)
[PDF] [Code] [Talk] [Slides] [Poster]

Distribution-Aware Binarization of Neural Networks for Sketch Recognition
Ameya Prabhu, Vishal Batchu, Aurobindo Munagala, Rohit Gajawada, Anoop Namboodiri
In WACV 2018 (Oral)
[PDF] [Code] [Talk] [Slides] [Poster]


Others

Towards sub-word level compositions for sentiment analysis of hindi-english code mixed text
Ameya Prabhu, Aditya Joshi, Manish Shrivastava, Vasudeva Varma
In COLING 2016
[PDF] [Poster] [Code]

Learning clustered sub-spaces for sketch-based image retrieval
Koustav Ghosal, Ameya Prabhu, Riddhiman Dasgupta, Anoop Namboodiri
In ACPR15 (Oral)
[PDF] [Slides]