Search Results for author: Kumar Shubham

Found 5 papers, 2 papers with code

Fusing Conditional Submodular GAN and Programmatic Weak Supervision

1 code implementation16 Dec 2023 Kumar Shubham, Pranav Sastry, Prathosh AP

In our work, we address these challenges by (i) implementing a noise-aware classifier using the pseudo labels generated by the label model (ii) utilizing the noise-aware classifier's prediction to train the label model and generate class-conditional images.

Constructing Bayesian Pseudo-Coresets using Contrastive Divergence

no code implementations20 Mar 2023 Piyush Tiwary, Kumar Shubham, Vivek Kashyap, Prathosh A. P

Bayesian Pseudo-Coreset (BPC) and Dataset Condensation are two parallel streams of work that construct a synthetic set such that, a model trained independently on this synthetic set, yields the same performance as training on the original training set.

Dataset Condensation

Weakly-Supervised Classification and Detection of Bird Sounds in the Wild.

1 code implementation CLEF 2021 Marcos V. Conde, Kumar Shubham, Prateek Agnihotri, Nitin D. Movva, Szilard Bessenyei

It is easier to hear birds than see them, however, they still play an essential role in nature and they are excellent indicators of deteriorating environmental quality and pollution.

Audio Classification Audio Tagging +3

Learning a Deep Reinforcement Learning Policy Over the Latent Space of a Pre-trained GAN for Semantic Age Manipulation

no code implementations2 Nov 2020 Kumar Shubham, Gopalakrishnan Venkatesh, Reijul Sachdev, Akshi, Dinesh Babu Jayagopi, G. Srinivasaraghavan

In our work, we have formulated a Markov Decision Process (MDP) over the latent space of a pre-trained GAN model to learn a conditional policy for semantic manipulation along specific attributes under defined identity bounds.

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