Search Results for author: Nikhil Verma

Found 6 papers, 1 papers with code

Neural Conversational QA: Learning to Reason vs Exploiting Patterns

no code implementations EMNLP 2020 Nikhil Verma, Abhishek Sharma, Dhiraj Madan, Danish Contractor, Harshit Kumar, Sachindra Joshi

Neural Conversational QA tasks such as ShARC require systems to answer questions based on the contents of a given passage.

Image Reconstruction using Enhanced Vision Transformer

no code implementations11 Jul 2023 Nikhil Verma, Deepkamal Kaur, Lydia Chau

The model proposed in this project is based on Vision Transformer (ViT) that takes 2D images as input and outputs embeddings which can be used for reconstructing denoised images.

Deblurring Image Denoising +2

Diffusion idea exploration for art generation

no code implementations11 Jul 2023 Nikhil Verma

With plethora of applications in diverse areas, generation of novel content using multiple modalities of data has remained a challenging problem.

Generative Adversarial Network Image Generation

Neural Conversational QA: Learning to Reason v.s. Exploiting Patterns

2 code implementations9 Sep 2019 Nikhil Verma, Abhishek Sharma, Dhiraj Madan, Danish Contractor, Harshit Kumar, Sachindra Joshi

On studying recent state-of-the-art models on the ShARCQA task, we found indications that the models learn spurious clues/patterns in the dataset.

Stability Based Filter Pruning for Accelerating Deep CNNs

no code implementations20 Nov 2018 Pravendra Singh, Vinay Sameer Raja Kadi, Nikhil Verma, Vinay P. Namboodiri

Convolutional neural networks (CNN) have achieved impressive performance on the wide variety of tasks (classification, detection, etc.)

Model Compression

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